Choosing Fair Value versus Historical Cost
Accounting Quality: Choosing Fair Value versus Historical Cost
CHEN Chen
School of Management, China University of Mining and Technology, P.R.China, 221116
Abstract: This paper compares accounting quality metrics for real estate firms to investigate whether the choice of investment property measurement model is associated with earnings management and lower value relevance. We examine the different accounting quality levels of different real estate firms which are classified
by investment property measurement under China’s new accounting standards from 2007 to 2009. We hypothesize and find evidence that the fair value firms have lower variance of change in net income, lower ratio of the variance of change in net income and change in cash flows, higher frequency of small positive net income, and lower value relevance. The empirical results indicate that real estate firms which adopt fair value model to measure investment property have lower accounting quality than other real estate firms. We also find that no fair value firm report negative net income. Overall, our results suggest that the adoption of fair value model should be considered carefully especially under China’s special market background.
Keywords: accounting quality, earnings management, fair value model, historical cost model, value relevance
1 Introduction
The adoption of China’s new accounting standards has deep impact on the listed companies’ financial statement. In particular, the investment property measurement choice of fair value model or historical cost model has greatly influence real estate companies’ financial reporting system. Upon adoption of new accounting standards, all listed companies have to choose
a measurement to treat their investment property. Under the fair value model, investment property is reported at fair value on the balance sheet, and all changes in fair value flow through the income statement. Under the cost model, investment property is reported at depreciated historical cost.
The question addressed is whether the application of fair value model results in accounting amounts that are of lower accounting quality than those resulting from application of historical cost model. We investigate whether fair value model firms exhibit more earnings management and lower value relevance than historical cost model firms. We collect data by hand from financial statements of 260 listed real estate companies. O nly 15 firms reported their property under fair value model. The empirical results reveal that firms choosing the fair value model are more likely to have earnings management and lower value relevance.
This study which makes comparisons of accounting quality is potential relevant to current debate of fair value accounting all over the world. Prior research finds that fair value has more value relevance than historical cost. However, under China’s special background, similar accounting policy may produce completely different results. Similar results can be found in other countries. After the adoption of fair value accounting and International Accounting Standards (IFRS/IAS) in Portugal, Oliveira [1] (2010) finds evidence the value relevance decreases. To our knowledge, our paper is the first to explicitly analyze the accounting quality of different accounting model companies. We contribute to the literature on accounting choice by assessing accounting quality of firms. There is rarely research focused on investment property’ accounting choice. This paper aims to this topic and summarizes the accounting quality of different firms which are grouped by accounting model. Our findings in this regard may suggest list companies to consider the investment property measurement model more carefully. In addition, this paper may help standard-setters and investors understand the situation of fair value accounting in China, and make reasonable decision.
The remainder of this paper is organized as follows. Section 2 provides background information and related literature. Section 3 presents our hypothesis development and research design. Section 4 discusses our sample selection and empirical results. Section 5 offers a summary and conclusion.
2 Background and related literature
China Securities Regulatory Commission (CASC) required China’s listed companies to choose between fair value or historical cost models to report their investment property in their primary financial statements from 1st January, 2007. However, the fair value model would likely introduce substantial volatility in reported net income. Owing to the booming market of China’s real estate, the fair value model would definitely bring
2011 International Conference on Management Science & Engineering (18th) September 13-15, 2011 Rome, Italy
positive net income to real estate firms. Actually, most listed companies prefer to continue the historical cost model. Chen [2] (2010) described that only 18 of 630 listed companies reported their investment property under the fair value model in 2007. As indicated in Tab.1, while most real estate companies have investment property, only 15 of 260 companies chose fair value from 2007 to 2009. It is surprised that more than 90 percent of companies choose cost model rather than fair value model which may bring more profits to real estate firms. Thus, it is doubtful whether the fair value model is suitable for China’s market.
Several studies make comparisons of fair value model and historical model. Barth[3] (1994) finds that the fair value explanation of investment securities is higher than historical cost one in bank industry. Biddle, Seow and Siegel[4] (1995) point out that the fair value is incrementally informative. Similarly, Khurana and Kim[5] (2003) compare relative explanatory power of fair value and historical cost in bank industry, but find that historical cost has better explanation than fair value in some aspects such as loans and deposits. Additionally, China’s accounting researchers also focus on this topic. Several prior researches indicate that fair value model is better than historical model and suggest that fair value would definitely domain the international accounting system (e.g. Wang, Song and Zhang[6] 2008, Zhao and Wang[7] 2009). Zhu, Liu and Li[8] (2010) discuss information view and measurement view to conclude that fair value measurement can provide more useful information to decisions.
Tab.1 Sample summary
Year Fair Value Firms Historical Cost Firms
2007 3 78
2008 5 80
2009 7 87
Total 15 245
A number of studies examine the account quality, most of which have focused on the voluntary adoption of International Accounting Standards (IAS). Barth, Landsman and Lang[9](2008) find that accounting quality of firms applying IAS generally is higher than that of firms applying domestic standards. Eccher and Healy[10] (2003) find differences in value relevance of accounting amounts based on IAS and Chinese standards depending on whether firms’ shares can be owned by Chinese or foreign investors. Harris and Muller[11] (1999) provide evidence that US General Accounting Standards (GAAP) reconciled amounts for 31 firms applying IAS are value relevant incremental to IAS-based accounting amounts.
Prior research also focused on the decision to voluntarily report fair value of non-financial assets. Muller[12](1999) examines UK firms’ voluntary decision to capitalize current value estimates of brand names acquired in a business combination, providing evidence that this decision reflects firms’ attempts to minimize the cost. Additionally, Dietrich, Harris and Muller[13] (2001), Muller and Riedl[14] (2002) both provide evidence that fair value estimate of UK property firms’ real estate assets as more reliable when external appraisers are employed. Lemke and Page[15](1992) conclude that the major motivation for compliance with a domestic standard requiring historical cost model was the ability to report lower income.
Several Chinese papers investigate fair value and investment property, most of which have focused on the application of new accounting standards (Wang and Jia[16] 2010;Li and Gao[17] 2010;Guan[18] 2010; Zheng[19] 2008). Prior papers also investigate the correlation between earnings management and fair value. Qiu[20](2010) provides empirical evidence that fair value model may affect asset value volatility and earnings management.
Until now no research has provided the evidence of the relationship between accounting quality and accounting models. Our paper is focus on accounting quality and fair value model choice. First, we build on the accounting quality literature by being the first paper to compare China’s real estate firms’ accounting quality. Second, we also build on the literature examining the actual situation of investment property measurement. Third, we build on the literature examining the applicability of fair value model under China’s market background.
3 Hypothesis and research design
3.1 Hypothesis
We expect firms’ accounting qualities are different between fair value model firms (FV firms) and historical cost model firms (HC firms). Accounting Quality stands a very broad category in accounting system which includes financial information system, accounting policy choice and application. We compare accounting quality metrics for real estate firms by earning smoothing metrics and value relevance metrics. Although most prior papers indicate that fair value model is more value relevance than cost model, different background and different markets may produce different results. Under the special China’s market background, based on the situation of accounting choice, we expect that the fair value model is not suitable to China’s listed companies, which may explain the reason why most companies didn’t choose fair value model.
Because the fair value model will generate the volatility of income, real estate may make use of fair value choice to manage earnings especially in China’s fast-growing and high price real estate market. In addition, the activity of China’s market and the accountants’ quality are limited, which means that the choice of fair value model may be irrational. Thus, we expect firms adopting fair value model have lower accounting quality than other firms. Particularly, we expect FV firms have higher possibility of earnings management. Regarding value relevance, we expect
firms with higher quality accounting amounts to have a higher association between stock price and earnings and equity book value because higher quality accounting amounts better reflect a firm’s underlying economics (Barth, Beaver, and Landsman [21], 2001).
H1: FV firms are more likely to engage in earnings management than HC firms.
H2: FV firms have lower level of value relevance than HC firms.
3.2 Research design
Based on the above discussion, we first compare the accounting quality with earnings management metrics. Our first earnings management metric is based on the variability of change in net income divided by total assets, 'NI (Lang, Raedy, and Wilson [22], 2006; Barth, Landsman, and Lang [9],2008). A smaller variance of change in net income is the evidence as the same as earnings smoothing. We include several control variables which also influence the variability of net income, and generate the model 1 as follows:
'NI it =0D +1D SIZE it +2D GROWTH it +3D EIS it +
4D DIS it +5D LEV it +6D TURN it +7D CF it +it H (1)
SIZE is the logarithm of firm’s market capitalization at the end of fiscal year. GROWTH is the percentage change of sales revenue. EIS is the percentage change of issued common stock. D IS is the percentage change of total debt. LEV is the total liabilities divided by firm’s equity. TURN is the sales revenue divided by total assets. CF is annual net cash flow from operations divided by total assets. Our variability metric is the variance of the residuals from the regression of equation (1). A lower variance of change in net income is related to higher possibility of earnings management. Thus, we estimate equation (1) and expect that the variance of residuals of FV firms (NIE) is lower than which of HC firms.
Firms with more volatile cash flows typically have more volatile net income, which means higher accounting quality. If firms use accruals to manage earnings, variability of change in net income should be lower than that of operating cash flows. Our second metric of earnings management is the ratio of variance of change in net income, to variance of change in cash flow from operations. We use a similar equation, but change the dependent variable into 'CF it .
'CF it =0D +1D SIZE it +2D GROWTH it +3D EIS it +
4D DIS it +5D LEV it +6D TURN it +7D CF it +it H (2)
'CF it is the change in net cash flow from
operations divided by total assets. We regress equation (2) and obtain the variance of residual (CFE). The second metric is the ratio of NIE to CFE (NICFE). According to the above discussion, we expect the ratio NICFE of FV firms is lower than which of HC firms.
Our third metric of earnings management is the coefficient on small positive net incomes in equation(3):
FV(0,1)it =0D +1D SPNI it +2D SIZE it +
3D GROWTH it +4D EIS it +5D DIS it +
6D LEV it +7D TURN it +8
D CF it +it H (3)
FV (0,1)it is an indicator variable that equals 1 for FV firms and 0 for HC firms. SPNI it is a dummy variable that equal 1 if net income divided total assets is between 0 and 0.01 (Lang, Raedy, and Yetman [23], 2003).We expect a positive coefficient on SPNI it which means that FV firms are more likely to use earnings management to control small net income.
According to the hypothesis, the value relevance metric is based on the regression of stock price on earnings and equity book value. If the firms have value relevance, the coefficient of regression is significant. Therefore, we expect the regression result of FV firms is not significant. In particular, if FV firms and HC firms both show the value relevance, we would use the adjusted R squared as the value relevance metric. A higher adjusted R squared of the regression indicates a better explanation power of the regression. As the discussion above, we expect an insignificant result or a lower adjusted R squared of FV firms’ regression. P it =0E +1E BVP it +2E EPS it +3E SIZE it +
4E Shares it +it P (4)
P it is the stock price on 30th April of the next fiscal year. BVP it is the book value of equity per share. EPS it is the earnings per share. SIZE it and Shares it are added in this equation as the control variables. SIZE it has already been defined. Shares it is the common stock percentage of firm i in year t. Because this paper only focuses on real estate industry, the influence of industries is ignored. We estimate equation (4) separately and test the significance of two firms’ samples.
4 Sample and empirical results
4.1 Sample selection
We select the financial statements from the websites of Shanghai Stock Exchange and Shenzhen Stock Exchange. Then we classify the real estate firms according to the choice of investment property by hand. We obtain the data from China Center for Economics Research (CCER) database. Because the new accounting standards are required to adopt from 2007, the available data are based on the financial information from 2007 to 2009. Since some real estate firms have no investment property, we first exclude these firms. In addition, assets reorganization may induce suspension and business transformation which may influence the reliability of our empirical results. Thus, we exclude the firms which witnessed IPO or asset reorganization. The result in our final sample of 260 listed real estate companies. Tab. 2 presents the sample selection process. We use STATA11 for data handling.
Tab.2 Sample selection
Number Real estate firms 370 Exclude observations without investment
property 92 Exclude observations with assets reconstruction
or IPO 18 Final sample 260 4.2 Descriptive statistics
Tab.3 provides descriptive statistics for FV firms and HC firms. It reveals that FV firms have lower asset turnover ratio (median 0.1690247 versus 0.253368) and higher frequency of small positive net income (mean 0.13333 versus 0.0326531). Tab. 3 also suggests FV firms and HC firms are similar in size, net income and sales revenue, which reflects effective of our matching procedure.
4.3 Results
Tab. 4 presents the results from our equations examining the accounting quality of sample firms. It reveals consistent evidence that FV firms have lower accounting quality than HC firms. In particular, all the metrics of earnings management are all significant different and in the predicted direction.
HC firms exhibit a higher variability of change in net income (NIE: 0.5551 versus0.0008); a higher ratio of change in net income, and change in cash flow from operations (NICFE: 0.0651 versus 0.0029). The results indicate that HC firms have less earnings smoothing. Additionally, results for managing toward positive net income are also consistent with FV firms managing earning more than HC firms. In particular, the coefficient on SPNI is significantly positive, which is consistent with our hypothesis.
The final finding in Tab.3 relates to value relevance of accounting amounts. First, the regression of stock price on earnings and equity book value for FV firms and HC firms reveal that the adjusted R squared for HC firms is higher than FV firms. It is consistent with the hypothesis. Furthermore, both the coefficients on earnings and equity book value for FV firms are insignificant in the regression, which indicates that the FV firms have lower value relevance. Therefore, the findings are consistent with accounting amounts being more value relevant for HC firms than for FV firms.
Tab.3 Descriptive statistics of sample
FV firms HC firms
Variables Mean Median Standard Deviation Mean Median Standard Deviation
SIZE 22.75863
22.6694
0.9021881
22.31617
22.26282
1.095313
Sales
revenue
1.74E+09
1.21E+09 1.82E+09
2.25E+09
1.03E+09 5.09E+09
Net
income 2.81E+08
1.30E+08 3.91E+08 3.32E+08
1.42E+08 7.23E+08
Stock Return -0.2531 0.5907 1.344039 -0.2852233 0.5375 1.418675
'NI 0.0092761 0.0108189 0.0126738 0.0090649 0.0090631 0.0510757
'CF 0.0124624 -0.0054607 0.1427695 0.1884318 0.0118624 31.56629
GROWTH -0.4296946
0.3343385 2.598783 -0.5841372
0.158277 5.205354
TURN 0.1812837
0.1690247 0.1180186 0.2827916
0.253368 0.2161975
LEV 1.386479
1.387412
0.7885446
1.986726
1.52147
2.017911
EIS 0.62107
1.024681
0.2544586
0.5607822 D
IS 0.057933
0.2338748
1.169595
0.1688466
0.1937989
0.6923996
SPNI 0.1333333
0 0.3518658
0.0326531
0 0.1780907
P 9.642667
9.9
4.29759
11.99735
10.83
5.839155
BVP 3.200567
1.87
2.137061
3.06946
2.52 2.44363
EPS 0.2382933
0.0102
0.1640995
0.3116829
0.27
0.3682152
Tab.4 Regression Results of Equations
FV firms HC firms
Earnings management NIE 0.0008 0.5551
NICFE 0.0029 0.0651
Coefficient on SPNI 0.1851**
(2.46) Value relevance
Adjust R squared 0.3462 0.3498 Coefficient on BVP 0.7003
0.8062***
(1.01) (5.27)
Coefficient on EPS -8.9133 2.815**
(0.79) (2.59) Coefficient on SIZE 0.0146
1.3032***
(0.01) (3.95)
Coefficient on Shares
-0.6457
-1.9155
(-0.15) (-1.37) *indicate significance at less than 10% level
**indicates significance at less than 5% level ***indicates significance at less than 1% level 4.4 Sensitivity analysis Prior work shows the variability of net income, net cash flow divided by total assets. Consequently, we drop
total assets, and use net income and net cash flow from
operations as dependent variables in equation (1) and (2).
The significance doesn’t change. The similar results are
also consistent with our hypothesis. Next, we use large
negative net income to test whether the FV firms
wouldn’t like to report loss. The equation (3) is replaced
as:
FV(0,1)it =0D +1D LNNI it +2D SIZE it +
3D GROWTH it +4D EIS it +5D DIS it + 6D LEV it +7D TURN it +8D CF it +it H (5) LNNI it is a dummy variable that equal 1 if net
income divided total assets is less than -0.2, and 0
otherwise. The low frequency of reporting lager negative
net income may inflect higher possibility of earnings
management. The regression result is not significant.
However, there is no FV firm reporting negative net
income in our sample. It may reveal that FV firms are
likely to manage earnings to avoid large loss. Although
we predict higher quality accounting results in a higher
frequency of large losses, the opposite could be true. In
particular, a higher frequency of large losses could be
indicative of big bath earnings management. Also, a
higher frequency of large losses could result from error
in estimating accruals. Thus, higher quality accounting
can result in a lower frequency of large losses. Therefore,
this result doesn’t overturn our hypothesis.
Owing to the relationship between earnings
management and accruals, we also use an earnings
smoothing metric which is based on the Spearman correlation between accruals and cash flows. Accrual
(ACC) is net income (NI) minus cash flows from
operations (CF). We use equation (6) and equation (7) to
estimate and compare the residuals (CFEE and ACCE). Since accruals are sensitive to earnings management, the correlation between CFEE and ACCE may reflect the
possibility of earnings management. If FV firms are
more likely to use earnings management, the correlation
of FV firms should be smaller than which of HC firms. CF it =0D +1D SIZE it +2D GROWTH it +3D EIS it +
4D DIS it +5D LEV it +6D TURN it +it H (6) ACC it =0D +1D SIZE it +2D GROWTH it +3D EIS it + 4D DIS it +5D LEV it +6D TURN it +it H (7)
We compare the Spearman correlation of residuals of equation (6) and equation (7). However, the
correlation of CFEE and ACCE of FV firms is -0.91,
while the correlation of HC firms is -0.93. The result is
not consistent with our hypothesis. There is no significant difference between FV firms and HC firms. However, the small difference also cannot change the whole result and turnover our hypothesis.
5 Conclusion
This paper examines the accounting quality of FV
firms and HC firms. This study compares the quality of
accounting amounts of firms that apply fair value that
apply historical cost model to measure investment
property. We exploit the earnings management and value
relevance of real estate firms to find the evidence of
different accounting quality. Overall, our results suggest that firms choosing fair value model are more likely to manage earnings. Additionally, the FV firms have lower
value relevance than HC firms. In particular, HC firms
have a significantly variance of change in net income, a
significantly higher ratio of the variance of change in net income and change in cash flows, and a significantly
higher value relevance of equity book value and earnings
for per share.
However, the sensitivity checks provide limited
evidence that FV firms are more likely to use earnings
management. The correlation test between accruals and
cash flows cannot support our hypothesis. But most of
our empirical results are consistent with hypothesis. To
sum up, consistent with hypothesis, we provide evidence
that quality of accounting amounts of real estate firms
choosing fair value model would be lower than that of
firms choosing historical model.
These findings may suggest China’s listed
companies to consider fair value model more carefully.
The findings also provide an insight to financial
statement users that the adoption fair value model may
reflect a lower accounting quality of listed firm.
Additionally, these insights may also assist standard
setters in modifying the standards to fit China’s market background. Although the adoption rules of fair value model is very restricting in China, the results also suggest CASC to reconsider the adoption of fair value model.
It is noted that the fair value model is prevalent and more value relevance in developed countries. However, these results suggest that fair value model may give birth to some negative effects in accounting quality of China’s listed companies. The same model and similar accounting policy generate opposite situations in different countries. That mainly because domestic market is deficient in the fair value, relevance, reliability and other aspects of the lack of significant. The time measured at fair value model as a major mode is not ripe, probably because the imperfect capital market in China, pricing and utilization channels, which have not been established. There is no standardized value established. Importantly, regulatory mechanism is not mature enough. How to make good use of the advantages of fair value and reduce or avoid the negative impact of Chinese market is to improve the experimental model. It will be a great deal to investigate the reason of these opposite situations in our future work.
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Excel函数公式完整版
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(完整word版)excel函数的说明及其详细的解释
excel 函数的说明及其详细的解释 数据库和清单管理函数 AVERAGE返回选定数据库项的平均值 DCOUNT计算数据库中包含数字的单元格的个数 DCOUNTA计算数据库中非空单元格的个数 DGET从数据库中提取满足指定条件的单个记录 DMAX返回选定数据库项中的最大值 DMIN返回选定数据库项中的最小值 DPRODUCT乘以特定字段（此字段中的记录为数据库中满足指定条件的记录）中的值 DSTDEV根据数据库中选定项的示例估算标准偏差 DSTDEVP根据数据库中选定项的样本总体计算标准偏差 DSUM对数据库中满足条件的记录的字段列中的数字求和 DVAR根据数据库中选定项的示例估算方差 DVARP根据数据库中选定项的样本总体计算方差 GETPIVOTDATA 返回存储在数据透视表中的数据
日期和时间函数 DATE返回特定时间的系列数 DATEDIF计算两个日期之间的年、月、日数 DATEVALUE 将文本格式的日期转换为系列数 DAY 将系列数转换为月份中的日 DAYS360按每年360 天计算两个日期之间的天数 EDATE返回在开始日期之前或之后指定月数的某个日期的系列数 EOMONTH返回指定月份数之前或之后某月的最后一天的系列数 HOUR将系列数转换为小时 MINUTE将系列数转换为分钟 MONTH将系列数转换为月 NETWORKDAYS 返回两个日期之间的完整工作日数 NOW 返回当前日期和时间的系列数 SECOND将系列数转换为秒 TIME返回特定时间的系列数 TIMEVALUE将文本格式的时间转换为系列数 TODAY返回当天日期的系列数 WEEKDAY将系列数转换为星期 WORKDAY返回指定工作日数之前或之后某日期的系列数YEAR 将系列数转换为年
电子表格常用函数公式
电子表格常用函数公式 1、自动排序函数： =RANK(第1数坐标，$第1数纵坐标$横坐标：$最后数纵坐标$横坐标，升降序号1降0升) 例如：=RANK(X3,$X$3:$X$155,0) 说明：从X3 到X 155自动排序 2、多位数中间取部分连续数值： =MID（该多位数所在位置坐标，所取多位数的第一个数字的排列位数，所取数值的总个数） 例如：612730************在B4坐标位置，取中间出生年月日，共8位数 =MID(B4，7，8) =19820711 说明：B4指该数据的位置坐标，7指从第7位开始取值，8指一共取8个数字 3、若在所取的数值中间添加其他字样， 例如：612730************在B4坐标位置，取中间出生年、月、日，要求****年**月**日格式 =MID(B4，7，4)&〝年〞&MID(B4，11，2) &〝月〞& MID(B4，13，2) &〝月〞&
=1982年07月11日 说明：B4指该数据的位置坐标，7、11指开始取值的第一位数排序号，4、2指所取数值个数，引号必须是英文引号。 4、批量打印奖状。 第一步建立奖状模板：首先利用Word制作一个奖状模板并保存为“奖状.doc”，将其中班级、姓名、获奖类别先空出，确保打印输出后的格式与奖状纸相符（如图1所示）。 第二步用Excel建立获奖数据库：在Excel表格中输入获奖人以及获几等奖等相关信息并保存为“奖状数据.xls”，格式如图2所示。 第三步关联数据库与奖状：打开“奖状.doc”，依次选择视图→工具栏→邮件合并，在新出现的工具栏中选择“打开数据源”，并选择“奖状数据.xls”，打开后选择相应的工作簿，默认为sheet1，并按确定。将鼠标定位到需要插入班级的地方，单击“插入域”，在弹出的对话框中选择“班级”，并按“插入”。同样的方法完成姓名、项目、等第的插入。 第四步预览并打印：选择“查看合并数据”，然后用前后箭头就可以浏览合并数据后的效果，选择“合并到新文档”可以生成一个包含所有奖状的Word文档，这时就可以批量打印了。
Excel函数名称解释大全..
Excel函数大全 数据库和清单管理函数 DAVERAGE 返回选定数据库项的平均值 DCOUNT 计算数据库中包含数字的单元格的个数 DCOUNTA 计算数据库中非空单元格的个数 DGET 从数据库中提取满足指定条件的单个记录 DMAX 返回选定数据库项中的最大值 DMIN 返回选定数据库项中的最小值 DPRODUCT 乘以特定字段（此字段中的记录为数据库中满足指定条件的记录）中的值 DSTDEV 根据数据库中选定项的示例估算标准偏差 DSTDEVP 根据数据库中选定项的样本总体计算标准偏差 DSUM 对数据库中满足条件的记录的字段列中的数字求和 DVAR 根据数据库中选定项的示例估算方差 DVARP 根据数据库中选定项的样本总体计算方差 GETPIVOTDATA 返回存储在数据透视表中的数据 日期和时间函数 DATE 返回特定时间的系列数 DATEDIF 计算两个日期之间的年、月、日数 DATEVALUE 将文本格式的日期转换为系列数 DAY 将系列数转换为月份中的日 DAYS360 按每年 360 天计算两个日期之间的天数 EDATE 返回在开始日期之前或之后指定月数的某个日期的系列数 EOMONTH 返回指定月份数之前或之后某月的最后一天的系列数 HOUR 将系列数转换为小时 MINUTE 将系列数转换为分钟
MONTH 将系列数转换为月 NETWORKDAYS 返回两个日期之间的完整工作日数 NOW 返回当前日期和时间的系列数 SECOND 将系列数转换为秒 TIME 返回特定时间的系列数 TIMEVALUE 将文本格式的时间转换为系列数 TODAY 返回当天日期的系列数 WEEKDAY 将系列数转换为星期 WORKDAY 返回指定工作日数之前或之后某日期的系列数 YEAR 将系列数转换为年 YEARFRAC 返回代表 start_date（开始日期）和 end_date（结束日期）之间天数的以年为单位的分数 DDE 和外部函数 CALL 调用动态链接库（DLL）或代码源中的过程 REGISTER.ID 返回已注册的指定 DLL 或代码源的注册 ID SQL.REQUEST 连接外部数据源，并从工作表中运行查询，然后将结果作为数组返回，而无需进行宏编程。 有关 CALL 和 REGISTER 函数的其他信息 工程函数 BESSELI 返回经过修改的贝塞尔函数 In（x） BESSELJ 返回贝塞尔函数 Jn（x） BESSELK 返回经过修改的贝塞尔函数 Kn（x） BESSELY 返回贝塞尔函数 Yn（x） xlfctBIN2DEC BIN2DEC 将二进制数转换为十进制数 BIN2HEX 将二进制数转换为十六进制数 BIN2OCT 将二进制数转换为八进制数 COMPLEX 将实系数和虚系数转换为复数 CONVERT 将一种度量单位制中的数字转换为另一种度量单位制
EXCEL表格函数公式大全
Excel常用函数公式及技巧搜集（常用的） 【身份证信息？提取】 从身份证号码中提取出生年月日 =TEXT(MID(A1,7,6+(LEN(A1)=18)*2),"#-00-00")+0 =TEXT(MID(A1,7,6+(LEN(A1)=18)*2),"#-00-00")*1 =IF(A2<>"",TEXT((LEN(A2)=15)*19&MID(A2,7,6+(LEN(A2)=18)*2),"#-00-00")+0,) 显示格式均为yyyy-m-d。（最简单的公式，把单元格设置为日期格式） =IF(LEN(A2)=15,"19"&MID(A2,7,2)&"-"&MID(A2,9,2)&"-"&MID(A2,11,2),MID(A2,7,4)&"-"&MID(A2,11,2)&"-"&MID(A2,13,2)) 显示格式为yyyy-mm-dd。（如果要求为“1995/03/29”格式的话，将”-”换成”/”即可） =IF(D4="","",IF(LEN(D4)=15,TEXT(("19"&MID(D4,7,6)),"0000年00月00日 "),IF(LEN(D4)=18,TEXT(MID(D4,7,8),"0000年00月00日")))) 显示格式为yyyy年mm月dd日。（如果将公式中“0000年00月00日”改成“0000-00-00”,则显示格式为yyyy-mm-dd） =IF(LEN(A1:A2)=18,MID(A1:A2,7,8),"19"&MID(A1:A2,7,6)) 显示格式为yyyymmdd。 =TEXT((LEN(A1)=15)*19&MID(A1,7,6+(LEN(A1)=18)*2),"#-00-00")+0 =IF(LEN(A2)=18,MID(A2,7,4)&-MID(A2,11,2),19&MID(A2,7,2)&-MID(A2,9,2)) =MID(A1,7,4)&"年"&MID(A1,11,2)&"月"&MID(A1,13,2)&"日" =IF(A1<>"",TEXT((LEN(A1)=15)*19&MID(A1,7,6+(LEN(A1)=18)*2),"#-00-00")) 从身份证号码中提取出性别 =IF(MOD(MID(A1,15,3),2),"男","女") （最简单公式） =IF(MOD(RIGHT(LEFT(A1,17)),2),"男","女") =IF(A2<>””,IF(MOD(RIGHT(LEFT(A2,17)),2),”男”,”女”),) =IF(VALUE(LEN(ROUND(RIGHT(A1,1)/2,2)))=1,"男","女") 从身份证号码中进行年龄判断 =IF(A3<>””,DATEDIF(TEXT((LEN(A3)=15*19&MID(A3,7,6+(LEN(A3)=18*2),”#-00-00”) ,TODAY(),”Y”),) =DATEDIF（A1，TODAY（），“Y”） （以上公式会判断是否已过生日而自动增减一岁） =YEAR(NOW())-MID(E2,IF(LEN(E2)=18,9,7),2)-1900 =YEAR(TODAY())-IF(LEN(A1)=15,"19"&MID(A1,7,2),MID(A1,7,4)) =YEAR(TODAY())-VALUE(MID(B1,7,4))&"岁" =YEAR(TODAY())-IF(MID(B1,18,1)="",CONCATENATE("19",MID(B1,7,2)),MID(B1,7,4)) 按身份证号号码计算至今天年龄
Excel常用的函数计算公式大全(一看就会)
EXCEL的常用计算公式大全 一、单组数据加减乘除运算： ①单组数据求加和公式：=（A1+B1） 举例：单元格A1：B1区域依次输入了数据10和5，计算：在C1中输入 =A1+B1 后点击键盘“Enter（确定）”键后，该单元格就自动显示10与5的和15。 ②单组数据求减差公式：=（A1-B1） 举例：在C1中输入 =A1-B1 即求10与5的差值5，电脑操作方法同上； ③单组数据求乘法公式：=（A1*B1） 举例：在C1中输入 =A1*B1 即求10与5的积值50，电脑操作方法同上； ④单组数据求乘法公式：=（A1/B1） 举例：在C1中输入 =A1/B1 即求10与5的商值2，电脑操作方法同上； ⑤其它应用： 在D1中输入 =A1^3 即求5的立方（三次方）； 在E1中输入 =B1^（1/3）即求10的立方根 小结：在单元格输入的含等号的运算式，Excel中称之为公式，都是数学里面的基本运算，只不过在计算机上有的运算符号发生了改变——“×”与“*”同、“÷”与“/”同、“^”与“乘方”相同，开方作为乘方的逆运算，把乘方中和指数使用成分数就成了数的开方运算。这些符号是按住电脑键盘“Shift”键同时按住键盘第二排相对应的数字符号即可显示。如果同一列的其它单元格都需利用刚才的公式计算，只需要先用鼠标左键点击一下刚才已做好公式的单元格，将鼠标移至该单元格的右下角，带出现十字符号提示时，开始按住鼠标左键不动一直沿着该单元格依次往下拉到你需要的某行同一列的单元格下即可，即可完成公司自动复制，自动计算。 二、多组数据加减乘除运算： ①多组数据求加和公式：(常用) 举例说明：=SUM（A1:A10）,表示同一列纵向从A1到A10的所有数据相加； =SUM（A1:J1）,表示不同列横向从A1到J1的所有第一行数据相加； ②多组数据求乘积公式：（较常用） 举例说明：=PRODUCT（A1:J1）表示不同列从A1到J1的所有第一行数据相乘； =PRODUCT（A1:A10）表示同列从A1到A10的所有的该列数据相乘； ③多组数据求相减公式：(很少用) 举例说明：=A1-SUM（A2:A10）表示同一列纵向从A1到A10的所有该列数据相减； =A1-SUM（B1:J1）表示不同列横向从A1到J1的所有第一行数据相减； ④多组数据求除商公式：(极少用) 举例说明：=A1/PRODUCT（B1:J1）表示不同列从A1到J1的所有第一行数据相除； =A1/PRODUCT（A2:A10）表示同列从A1到A10的所有的该列数据相除； 三、其它应用函数代表： ①平均函数 =AVERAGE（:）；②最大值函数 =MAX （:）；③最小值函数 =MIN （:）； ④统计函数 =COUNTIF（:）：举例：Countif ( A1：B5，”>60”) 说明：统计分数大于60分的人数，注意，条件要加双引号，在英文状态下输入。
全尺寸检验作业指导书
XX 有限公司作业文件 文件编号：JT/C-8.2.4J-006 版号：A/0 全尺寸检验作业 指导书 批准： 审核： 编制： 受控状态：分发号： 2006年11月15 日发布2006年11月15日实施
全尺寸检验指导书JT/C-8.2.4J-006 1. 目的 根据顾客的要求和/或本公司控制计划的要求，规定合理的全尺寸检验的频次，使公司所生产产品的全过程，包括从原材料接收、生产、成品入库直到出厂，得到有效的控制。 2. 适用范围 本程序适用本公司的所有产品的全尺寸检验。 3. 职责 3.1 技术科负责制定合理的产品/材料的性能试验和全尺寸检测项目指标。 3.2 检验科负责产品和/或材料的性能试验和产品进行全尺寸检验。 3.3车间或仓库负责配合全尺寸检验的实施。 4.全尺寸检验的时机 4.1全尺寸检验要求的确定。 4.1.1根据公司产品特性和风险、品种数量的多少、质量的稳定性、顾客的要求等确定全尺寸检验的频次： 1. 根据顾客的要求的频次对所有的产品进行全尺寸检验和试验。 2. 根据技术科的要求对于产品和模具在长期停放后做全尺寸检验和 试验。 3.根据控制计划的要求进行全尺寸检验。 4.1.2当出现内部或外部客户抱怨、监测系统反应质量出现异常波动时，应考虑追加全尺寸检验的频次。 5全尺寸检验的实施 5.1全尺寸检验的資料输入 ?图纸; ?技术规范; ?生产工艺文件,生产过程描述; ?检验技术规范; ?缺陷目录(缺陷评定，例如︰主要和次要缺陷); ?极限样品; ?评定方法要求; 5.2 全尺寸检验的抽样要求 5.2.1全尺寸检验应在最近的生产批中进行，这是为了能够了解最新生产过程的影响。 5.2.2用于全尺寸检验的零件要直接从仓库中或从准备交付给顾客的原包装中抽样，以便能同时对装箱质量、包装清洁与否进行评价。检测结果进行
Excel函数详解解读
Excel 函数（按字母顺序列出） 函数名称类型和说明 ABS 函数数学和三角：返回数字的绝对值 ACCRINT 函数财务：返回定期支付利息的债券的应计利息ACCRINTM 函数财务：返回在到期日支付利息的债券的应计利息ACOS 函数数学和三角：返回数字的反余弦值 ACOSH 函数数学和三角：返回数字的反双曲余弦值ACOT 函数 数学和三角：返回数字的反余切值 ACOTH 函数 数学和三角：返回数字的反双曲余切值 AGGREGATE 函数数学和三角：返回列表或数据库中的聚合 ADDRESS 函数查找和引用：以文本形式将引用值返回到工作表的单个单元格 AMORDEGRC 函数财务：使用折旧系数返回每个记帐期的折旧值AMORLINC 函数财务：返回每个记帐期的折旧值 AND 函数逻辑：如果其所有参数均为TRUE，则返回TRUE ARABIC 函数 数学和三角：将罗马数字转换为阿拉伯数字 AREAS 函数查找和引用：返回引用中涉及的区域个数 ASC 函数文本：将字符串中的全角（双字节）英文字母或片假名更改为半角（单字节）字符 ASIN 函数数学和三角：返回数字的反正弦值 ASINH 函数数学和三角：返回数字的反双曲正弦值 ATAN 函数数学和三角：返回数字的反正切值 ATAN2 函数数学和三角：返回X 和Y 坐标的反正切值ATANH 函数数学和三角：返回数字的反双曲正切值 AVEDEV 函数统计：返回数据点与它们的平均值的绝对偏差平均值AVERAGE 函数统计：返回其参数的平均值 AVERAGEA 函数统计：返回其参数的平均值，包括数字、文本和逻辑值
函数名称类型和说明 AVERAGEIF 函数统计：返回区域中满足给定条件的所有单元格的平均值（算术平均值） AVERAGEIFS 函数统计：返回满足多个条件的所有单元格的平均值（算术平均值）。 BAHTTEXT 函数文本：使用?（泰铢）货币格式将数字转换为文本 BASE 函数数学和三角：将数字转换为具备给定基数(base) 的文本表示 BESSELI 函数工程：返回修正的贝赛耳函数In(x) BESSELJ 函数工程：返回贝赛耳函数Jn(x) BESSELK 函数工程：返回修正的贝赛耳函数Kn(x) BESSELY 函数工程：返回贝赛耳函数Yn(x) BETADIST 函数 兼容性：返回beta 累积分布函数 在Excel 2007 中，这是一个统计函数。 BETA.DIST 函数 统计：返回beta 累积分布函数 BETAINV 函数 兼容性：返回指定beta 分布的累积分布函数的反函数 在Excel 2007 中，这是一个统计函数。 BETA.INV 函数 统计：返回指定beta 分布的累积分布函数的反函数BIN2DEC 函数工程：将二进制数转换为十进制数 BIN2HEX 函数工程：将二进制数转换为十六进制数 BIN2OCT 函数工程：将二进制数转换为八进制数 BINOMDIST 函数 兼容性：返回一元二项式分布的概率 在Excel 2007 中，这是一个统计函数。 BINOM.DIST 函数 统计：返回一元二项式分布的概率 BINOM.DIST.RANGE 函数 统计：使用二项式分布返回试验结果的概率
excel表格常用的函数公式
e x c e l表格常用的函数公 式 Prepared on 22 November 2020
1、如何一次性去掉诸多超链接 选中所有的超链接，按住Ctrl+c再按Enter键，就取消的所有的超链。 2、如何在每行的下面空一行 如A1列有内容，我们需要在B1、C2单元格输入1，选中周边四格 ，然后向下拉，填充序列，然后在选取定位条件，选中空值，最后点击插入行，就行了。 3、删除一列的后缀
若A1为此，在B1单元格输入=LEFT（A1，LEN （A1）-4），然后下拉填充公式。 删除前缀则相反RIGHT 4、把多个单元格串成一句 运用=CONCATENATE（“A1”，“B2”，“C2”），比如A1,B1单元格分别是8，个，我们可在C1单元格输入=CONCATENATE("我有",A1,B1,"苹果")，随即C1单元格显示我有8个苹果。 5、数据分类汇总后按需排序 在数据分类汇总后，我们选择左侧2，把数据折叠起来，然后选中你按需排序规则的那行，点击排序即可。 6、分类汇总后，只复制汇总的项 在把分类汇总后的数据折叠后（只显示分类汇总项），然后选中这些，定位——可见单元格——复制——黏贴即可。 7、【Vlookup函数】查找制定目标的相对应数值 公式：B13=VLOOKUP(A13,$B$2:$D$8,3,0) A13是所需要的值对应的属性（姓名）；$B$2:$D$8是指查找的范围从B2开始一直到D8的区间范围内；3是指查找范围的第三列，即查找值所在的列；0表示精确查找或者也可填写false。 8、【sumif函数】在一定条件下求和 G2=sumif（D2：D8，”>=95”）
Excel表格函数公式大全
E x c e l表格函数公式大全-标准化文件发布号：（9456-EUATWK-MWUB-WUNN-INNUL-DDQTY-KII
目录按顺序整理，便于打印学习 EXCEL函数大全 (3) 1.数据库和清单管理函数 (3) 2.日期和时间函数 (3) 3.DDE 和外部函数 (4) 4.工程函数 (4) Excel2003常用函数 (6) 5.ABS函数 (6) 6.AND (7) 7.AVERAGE (7) 8.CELL (8) 9.CHOOSE (8) 10.COLUMN 函数 (9) 11.CONCATENATE函数 (9) 12.COUNT (10) 13.COUNTA (10) 14.COUNTIF (10) 15.DATEDIF函数 (11) 16.DATE函数 (11) 17.DAY函数 (12) 18.DCOUNT函数 (12) 19.FIND (13) 20.FREQUENCY函数 (13) 21.IF (13) 22.INDEX (14) 23.INT (15) 24.ISERROR函数 (16) 25.ISEVEN (16) 26.ISODD (17) https://www.sodocs.net/doc/5b17760060.html,RGE (17) 28.LEFT或LEFTB (17) 29.LEN或LENB (18) 30.LOOKUP (18) 31.MATCH (19) 32.MAX (20) 33.MIN (21) 34.MEDIAN (21) 35.MID或MIDB (22) 36.MOD函数 (22) 37.MONTH函数 (23) 38.NOW (23) 39.OR (24) 40.RAND (24) 41.RANK函数 (25) 42.RIGHT或RIGHTB (25) 43.ROUND (26) 44.SUBTOTAL函数 (26) 45.SUM (27) 46.SUMIF (27) 47.TEXT (28) 48.TODAY (29) 49.VALUE (29) 50.VLOOKUP (30) 51.WEEKDAY函数 (31) 关于EXCEL中函数COUNT的用法 (31)
Excel表格乘法函数公式
更多课程传送门：点这里 Excel表格乘法函数公式 时间:2011-04-05 来源:Word联盟阅读:21051次评论18条 在Excel表格中，我们常常会利用Excel公式来统计一些报表或数据等，这时就少不了要用到加、减、乘、除法，在前面我们已经详细的讲解了Excel求和以及求差公式使用方法。那么我们又如何利用公式来对一些数据进行乘法计算呢？怎样快速而又方便的来算出结果呢？下面Word联盟就来教大家一步一步的使用Excel乘法公式！ 我们先从简单的说起吧！首先教大家在A1*B1=C1，也就是说在第一个单元格乘以第二个单元格的积结果会显示在第三个单元格中。 1、A1*B1=C1的Excel乘法公式 ①首先，打开表格，在C1单元格中输入“=A1*B1”乘法公式。 ②输入完毕以后，我们会发现在 C1 单元格中会显示“0”，当然了，因为现在还没有输入要相乘的数据嘛，自然会显示0了。
③现在我们在“A1”和“B1”单元格中输入需要相乘的数据来进行求积，如下图，我分别在A1和B1单元格中输入10和50进行相乘，结果在C1中就会显示出来，等于“500”。 上面主要讲解了两个单元格相乘求积的方法，但是在我们平常工作中，可能会遇到更多数据相乘，下面主要说说多个单元格乘法公式运用，如：
“A1*B1*C1*D1”=E1。 2、Excel中多个单元格相乘的乘法公式 ①在E1单元格中输入乘法公式“=A1*B1*C1*D1”。 ②然后依次在A1、B1、C1、D1中输入需要相乘的数据，结果就会显示在“E1”中啦！
看看图中的结果是否正确呀！其实，这个方法和上面的差不多，只不过是多了几道数字罢了。 因为在工作中不止是乘法这么简单，偶尔也会有一些需要“加减乘除”一起运算的时候，那么当遇到这种混合运算的时候我们应当如何来实现呢？这里就要看你们小学的数学有没学好了。下面让我们一起来做一道小学时的数学题吧！ 3、Excel混合运算的乘法公式，5加10减3乘2除3等于多少？ 提示：加=+，减=-，乘=*，除=/。 ①首先，我们要了解这个公式怎么写，“5+10-3*2/3”这是错误的写法，正确写法应该是“（5+10-3）*2/3”。 ②好了，知道公式了，我们是不是应该马上来在Excel中的“F1”中输入“=(A1+B1-C1)*D1/E1”。 ③然后依次在A1、B1、C1、D1、E1中输入需要运算的数据。
Excel函数应用解读
目录 第1章Excel函数基础 1 1.1Excel 2003的基础知识 1 1.1.1工作簿、工作表与单元格 1 1.1.2函数与参数 3 1.2单元格的引用 3 1.2.1A1和R1C1引用样式 3 1.2.2绝对引用、相对引用和混合引用 5 1.2.3三维引用8 1.3使用公式10 1.3.1公式的基本元素10 1.3.2常见运算符10 1.3.3公式的使用12 1.3.4为公式命名14 1.4使用函数16 1.5函数的分类19 第2章数学与三角函数21 1．返回数字的绝对值：ABS21 2．返回数字的反余弦值：ACOS21 3．返回数字的反双曲余弦值：ACOSH22 4．返回数字的反正弦值：ASIN22 5．返回数字的反双曲正弦值：ASINH23 6．返回数字的反正切值：ATAN24 7．返回给定坐标值的反正切值：ATAN224 8．返回数字的反双曲正切值：ATANH25 9．按条件向上舍入：CEILING26 10．计算组合数：COMBIN27 11．计算余弦值：COS28 12．计算数字的双曲余弦值：COSH28 13．将弧度转换为度：DEGREES29
14．将数字舍入为偶数：EVEN29 15．返回e的n次幂：EXP30 16．计算数字的阶乘：FACT31 17．计算数字的双倍阶乘：FACTDOUBLE31 18．按条件向下舍入：FLOOR32 19．返回最大公约数：GCD33 20．将数字向下舍入取整：INT34 21．返回最小公倍数：LCM34 22．返回数字的自然对数：LN35 23．返回指定底数的对数：LOG35 24．返回以10为底的对数：LOG1036 25．返回数组的矩阵行列式值：MDETERM36 26．返回数组矩阵的逆矩阵：MINVERSE37 27．返回矩阵的乘积：MMULT39 28．求两数的余数：MOD39 29．返回按指定基数舍入数值：MROUND40 30．返回和的阶乘与阶乘乘积的比值：MULTINOMIAL41 31．返回舍入奇数：ODD42 32．返回数学常量：PI43 33．返回数字的乘幂：POWER43 34．返回乘积值：PRODUCT44 35．返回商的整数部分：QUOTIENT45 36．返回弧度值：RADIANS45 37．返回随机数：RAND46 38．返回指定两数之间的随机数：RANDBETWEEN46 39．转换成文本形式罗马数字：ROMAN47 40．返回按指定位数四舍五入的数字：ROUND48 41．向下舍入数字：ROUNDDOWN48 42．向上舍入数字：ROUNDUP49 43．返回幂级数之和：SERIESSUM50 44．返回数字的符号：SIGN50
Excel函数公式
Excel函数公式 在会计同事电脑中，保保经常看到海量的Excel表格，员工基本信息、提成计算、考勤统计、合同管理.... 看来再完备的会计系统也取代不了Excel表格的作用。 于是，小呀尽可能多的收集会计工作中的Excel公式，所以就有了这篇本平台史上最全的Excel公式+数据分析技巧集。 员工信息表公式 1、计算性别(F列) =IF(MOD(MID(E3,17,1),2),"男","女") 2、出生年月(G列) =TEXT(MID(E3,7,8),"0-00-00") 3、年龄公式(H列) =DATEDIF(G3,TODAY,"y") 4、退休日期(I列) =TEXT(EDATE(G3,12*(5*(F3="男")+55)),"yyyy/mm/dd aaaa") 5、籍贯(M列) =VLOOKUP(LEFT(E3,6)*1,地址库!E:F,2,) 注：附带示例中有地址库代码表 6、社会工龄(T列) =DATEDIF(S3,NOW,"y") 7、公司工龄(W列) =DATEDIF(V3,NOW,"y")&"年"&DATEDIF(V3,NOW,"ym")&"月"&DATEDIF(V3,NOW,"md")&"天" 8、合同续签日期(Y列) =DATE(YEAR(V3)+LEFTB(X3,2),MONTH(V3),DAY(V3))-1 9、合同到期日期(Z列) =TEXT(EDATE(V3,LEFTB(X3,2)*12)-TODAY,"[<0]过期0天;[<30]即将到期0天;还早") 10、工龄工资(AA列) =MIN(700,DATEDIF($V3,NOW,"y")*50) 11、生肖(AB列) =MID("猴鸡狗猪鼠牛虎兔龙蛇马羊",MOD(MID(E3,7,4),12)+1,1) 1、本月工作日天数(AG列) =NETWORKDAYS(B$5,DATE(YEAR(N$4),MONTH(N$4)+1,),) 2、调休天数公式(AI列) =COUNTIF(B9:AE9,"调") 3、扣钱公式(AO列) 婚丧扣10块，病假扣20元，事假扣30元，矿工扣50元 =SUM((B9:AE9={"事";"旷";"病";"丧";"婚"})*{30;50;20;10;10}) 1、本科学历人数 =COUNTIF(D:D,"本科") 2、办公室本科学历人数 =COUNTIFS(A:A,"办公室",D:D,"本科") 3、30~40岁总人数 =COUNTIFS(F:F,">=30",F:F,"<40") 1、提成比率计算 =VLOOKUP(B3,$C$12:$E$21,3)
Excel表格公式使用基本操作及excel表格计算公式大全使用技巧要点
Excel 部分函数列表. AND “与”运算，返回逻辑值，仅当有参数的结果均为逻辑“真（TRUE）”时返回逻辑“真（TRUE）”，反之返回逻辑“假（FALSE）”。条件判断 AVERAGE 求出所有参数的算术平均值。数据计算 COLUMN 显示所引用单元格的列标号值。显示位置 CONCATENATE 将多个字符文本或单元格中的数据连接在一起，显示在一个单元格中。字符合并 COUNTIF 统计某个单元格区域中符合指定条件的单元格数目。条件统计 DATE 给出指定数值的日期。显示日期 DATEDIF 计算返回两个日期参数的差值。计算天数 DAY 计算参数中指定日期或引用单元格中的日期天数。计算天数 DCOUNT 返回数据库或列表的列中满足指定条件并且包含数字的单元格数目。条件统计 FREQUENCY 以一列垂直数组返回某个区域中数据的频率分布。概率计算 IF 根据对指定条件的逻辑判断的真假结果，返回相对应条件触发的计算结果。条件计算 INDEX 返回列表或数组中的元素值，此元素由行序号和列序号的索引值进行确定。数据定位 INT 将数值向下取整为最接近的整数。数据计算 ISERROR 用于测试函数式返回的数值是否有错。如果有错，该函数返回TRUE， 反之返回FALSE。逻辑判断 LEFT 从一个文本字符串的第一个字符开始，截取指定数目的字符。截取数据LEN 统计文本字符串中字符数目。字符统计 MATCH 返回在指定方式下与指定数值匹配的数组中元素的相应位置。匹配位置MAX 求出一组数中的最大值。数据计算 MID 从一个文本字符串的指定位置开始，截取指定数目的字符。字符截取 MIN 求出一组数中的最小值。数据计算 MOD 求出两数相除的余数。数据计算 MONTH 求出指定日期或引用单元格中的日期的月份。日期计算 NOW 给出当前系统日期和时间。显示日期时间 OR 仅当所有参数值均为逻辑“假（FALSE）”时返回结果逻辑“假（FALSE）”，否则都返回逻辑“真（TRUE）”。逻辑判断 RANK 返回某一数值在一列数值中的相对于其他数值的排位。数据排序 RIGHT 从一个文本字符串的最后一个字符开始，截取指定数目的字符。字符截取 SUBTOTAL 返回列表或数据库中的分类汇总。分类汇总 SUM 求出一组数值的和。数据计算 SUMIF 计算符合指定条件的单元格区域内的数值和。条件数据计算 TEXT 根据指定的数值格式将相应的数字转换为文本形式数值文本转换 TODAY 给出系统日期显示日期 VALUE 将一个代表数值的文本型字符串转换为数值型。文本数值转换
Excel电子表格计算公式使用方法25条公式技巧总结
Excel电子表格计算公式使用方法25条公式技巧总结 对于Excel表格计算公式的方法实在太多，今天就整理了一个公式大全需要对有需要的朋友有些帮助。 1、两列数据查找相同值对应的位置 =MATCH(B1,A:A，0) 2、已知公式得结果 定义名称=EVALUATE(Sheet1!C1) 已知结果得公式 定义名称=GET.CELL(6,Sheet1!C1) 3、强制换行 用Alt+Enter 4、超过15位数字输入 这个问题问的人太多了，也收起来吧。一、单元格设置为文本;二、在输入数字前先输入'
5、如果隐藏了B列，如果让它显示出来？ 选中A到C列，点击右键，取消隐藏 选中A到C列，双击选中任一列宽线或改变任一列宽 将鼠标移到到AC列之间，等鼠标变为双竖线时拖动之。 6、EXCEL中行列互换 复制，选择性粘贴，选中转置，确定即可 7、Excel是怎么加密的 （1）、保存时可以的另存为>>右上角的"工具">>常规>>设置 （2）、工具>>选项>>安全性 8、关于COUNTIF COUNTIF函数只能有一个条件，如大于90，为=COUNTIF(A1:A10,">=90")
介于80与90之间需用减，为 =COUNTIF(A1:A10,">80")-COUNTIF(A1:A10,">90") 9、根据身份证号提取出生日期 （1）、 =IF(LEN(A1)=18,DATE(MID(A1,7,4),MID(A1,11,2),MID(A1,13,2)),IF(LEN(A1) =15,DATE(MID(A1,7,2),MID(A1,9,2),MID(A1,11,2)),"错误身份证号")) （2）、=TEXT(MID(A2,7,6+(LEN(A2)=18)*2),"#-00-00")*1 10、想在SHEET2中完全引用SHEET1输入的数据 工作组，按住Shift或Ctrl键，同时选定Sheet1、Sheet2 11、一列中不输入重复数字 [数据]--[有效性]--[自定义]--[公式] 输入=COUNTIF(A:A,A1)=1 如果要查找重复输入的数字 条件格式》公式》=COUNTIF(A:A,A5)>1》格式选红色
excel函数的说明及其详细的解释
excel函数的说明及其详细的解释 数据库和清单管理函数 AVERAGE 返回选定数据库项的平均值 DCOUNT 计算数据库中包含数字的单元格的个数 DCOUNTA 计算数据库中非空单元格的个数 DGET 从数据库中提取满足指定条件的单个记录 DMAX 返回选定数据库项中的最大值 DMIN 返回选定数据库项中的最小值 DPRODUCT 乘以特定字段（此字段中的记录为数据库中满足指定条件的记录）中的值 DSTDEV 根据数据库中选定项的示例估算标准偏差 DSTDEVP 根据数据库中选定项的样本总体计算标准偏差 DSUM 对数据库中满足条件的记录的字段列中的数字求和 DVAR 根据数据库中选定项的示例估算方差 DVARP 根据数据库中选定项的样本总体计算方差 GETPIVOTDATA 返回存储在数据透视表中的数据
日期和时间函数 DATE 返回特定时间的系列数 DATEDIF 计算两个日期之间的年、月、日数 DATEVALUE 将文本格式的日期转换为系列数 DAY 将系列数转换为月份中的日 DAYS360 按每年360天计算两个日期之间的天数 EDATE 返回在开始日期之前或之后指定月数的某个日期的系列数EOMONTH 返回指定月份数之前或之后某月的最后一天的系列数HOUR 将系列数转换为小时 MINUTE 将系列数转换为分钟 MONTH 将系列数转换为月 NETWORKDAYS 返回两个日期之间的完整工作日数 NOW 返回当前日期和时间的系列数 SECOND 将系列数转换为秒 TIME 返回特定时间的系列数 TIMEVALUE 将文本格式的时间转换为系列数 TODAY 返回当天日期的系列数 WEEKDAY 将系列数转换为星期 WORKDAY 返回指定工作日数之前或之后某日期的系列数 YEAR 将系列数转换为年
电子表格常用函数公式及用法
电子表格常用函数公式及用法 1、求和公式： =SUM(A2:A50) ——对A2到A50这一区域进行求和； 2、平均数公式： =AVERAGE(A2:A56) ——对A2到A56这一区域求平均数； 3、最高分： =MAX(A2:A56) ——求A2到A56区域（55名学生）的最高分；4、最低分： =MIN(A2:A56) ——求A2到A56区域（55名学生）的最低分； 5、等级： =IF(A2>=90,"优",IF(A2>=80,"良",IF(A2>=60,"及格","不及格"))) 6、男女人数统计： =COUNTIF(D1:D15,"男") ——统计男生人数 =COUNTIF(D1:D15,"女") ——统计女生人数 7、分数段人数统计： 方法一： 求A2到A56区域100分人数：=COUNTIF(A2:A56,"100") 求A2到A56区域60分以下的人数；=COUNTIF(A2:A56,"<60") 求A2到A56区域大于等于90分的人数；=COUNTIF(A2:A56,">=90") 求A2到A56区域大于等于80分而小于90分的人数； =COUNTIF(A1:A29,">=80")-COUNTIF(A1:A29," =90")
求A2到A56区域大于等于60分而小于80分的人数； =COUNTIF(A1:A29,">=80")-COUNTIF(A1:A29," =90") 方法二： （1）=COUNTIF(A2:A56,"100") ——求A2到A56区域100分的人数；假设把结果存放于A57单元格； （2）=COUNTIF(A2:A56,">=95")－A57 ——求A2到A56区域大于等于95而小于100分的人数；假设把结果存放于A58单元格；（3）=COUNTIF(A2:A56,">=90")－SUM(A57:A58) ——求A2到A56区域大于等于90而小于95分的人数；假设把结果存放于A59单元格； （4）=COUNTIF(A2:A56,">=85")－SUM(A57:A59) ——求A2到A56区域大于等于85而小于90分的人数； …… 8、求A2到A56区域优秀率：=(COUNTIF(A2:A56,">=90"))/55*100 9、求A2到A56区域及格率：=(COUNTIF(A2:A56,">=60"))/55*100 10、排名公式： =RANK(A2，A$2:A$56) ——对55名学生的成绩进行排名； 11、标准差：=STDEV(A2:A56) ——求A2到A56区域(55人)的成绩波动情况（数值越小，说明该班学生间的成绩差异较小，反之，说明该班存在两极分化）； 12、条件求和：=SUMIF(B2:B56,"男"，K2:K56) ——假设B列存放学生的性别，K列存放学生的分数，则此函数返回的结果表示求该班
全尺寸检验规范
Subject：
Subject： 1.0 目的 本规范是为了规范产品全尺寸检测过程，用以验证产品与技术标准之间的符合性。防止缺陷产品流入客户，保证为客户提供合格产品。 2.0 适用范围 本规范适用于公司现交付的所有产品的全尺寸检测。 3.0 职责 品质部负责全尺寸检测规范的实施工作。 其他部门负责协助品质部开展本项工作。 4.0 工作程序 4.1 品质部于每年12月25日前拟制次年的《年度产品全尺寸检测计划》，经部门经理审核，主管领导批准后下发实施。若在实施过程中，有新增加的产品，需纳入当月的《月度全尺寸检测计划》。 4.2 检验人员根据《年度产品全尺寸检测计划》、《月度全尺寸检测计划》和产品图纸对产品进行全尺寸检测。检测结果记录于产品成绩检查表上。检测结果完全符合图纸要求后，将相关的质量记录进行归档处理。 4.3 若检验人员在检测过程中，发现实物尺寸与图纸要求不相符时，应通知生产现场、库房、品质部对该产品进行不合格品标识、隔离。如果该产品已经发往客户，应立即告知客户，然后根据客户要求进行处理。 4.4 检测人员开具《纠正/预防措施报告单》，明确责任单位和责任人，要求责任单位对异常进行处理。 4.5 责任单位对异常处理完成后，由检测人员对处理后的效果进行确认，（确认内容至少包括：与样件尺寸是否相符）；不合格的要求责任单位重新处理。 4.6 检测人员于每月25日前，对当月的全尺寸检测结果进行归纳、总结并形成《检查成绩表》。同时将相关的质量记录进行归档处理。 4.7 品质部检验人员每天对交首件的零件进行全尺寸检测，如发现异常，请技术人员进行判
Subject： 定并对判定结果进行签字确认。 5.0 附件 全尺寸检测流程（附件一） 6.0 相关文件 《不合格品控制程序》 7.0 质量记录 7.1 QC-PZ11-001A《纠正/预防措施报告单》