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STATISTICAL FUNCTIONS IN EXCEL

发布时间:2023-06-16

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STATISTICAL FUNCTIONS IN EXCEL

In this appendix, we discuss the statistical functions in Excel that are useful for the material in this text. They will be referenced by Chapter within the text.

The statistical functions can be accessed by clicking on fx at the main menu and then clicking on Statistical Functions in the next submenu. At the next submenu you click on the statistical function you want. Each statistical function has its own submenu where the user supplies the appropriate parameters for the function to work on. These parameters usually include column locations within the spreadsheet where the data lie and in some cases other parameters needed by the function. Before clicking on fx , the cell where the result from using the function should be placed should be the active cell in the spreadsheet. A nice feature of Excel is that if a cell is made active, then the formula bar displays the function used to compute the result for that cell. Thus, all calculations are self-documented for further reference. There are other statistical commands that are available in the Tools menu, Data Analysis sub-menu. There are beyond the scope of this appendix.

CHAPTER 2 Descriptive Statistics

We have entered the cholesterol levels before adopting a vegetarian diet from Table 2.1 (study guide, Chapter  2) in Table A. 1 in cells C5–C28. To  compute  the  arithmetic  mean,  click  on fx ,  Statistical Functions, and then Average. Another screen will appear asking for the range of columns defining the dataset where the average is to be computed. Since the 1st value is in C5 and the last value is in C28, we enter C5:C28. The arithmetic mean is displayed to the right of Average(C5:C28). A similar approach is used for the median  (median), standard deviation  (Stdev), Variance  (Var) and Geometric Mean (GeoMean). To compute specific percentiles, we specify the range of data columns (i.e., C5:C28) and then the percentile desired which must be between 0 and 1. The 10th (153. 1) and 90th (237.4) percentiles are given in the spreadsheet.

CHAPTER 4 Discrete Probability Distributions

BINOMDIST

BINOMDIST  is  the  statistical  function  used  to  compute  individual  probabilities  and  cumulative probabilities for the binomial distribution. Suppose we want to compute the probability of 5 successes (k) in 26 trials (n), where the probability of success on one trial is .34 (p). The function BINOMDIST requires 4 parameters to perform this computation. The 1st parameter is k; the 2nd parameter is n; the 3rd parameter is p; the 4th parameter is the word TRUE if a cumulative probability is desired or the word FALSE if an individual probability is desired. Thus, in this case, we specify BINOMDIST(5, 26, .34, FALSE) = .049 (see  Table  A.2).  If  instead  we  want  the  probability  of  obtaining  ≤  5  successes,  then  we  specify BINOMDIST(5, 26, .34, TRUE) = .079. To obtain the probability of ≥ 6 successes, we simply subtract from l and obtain .921.

Table A.1 Cholesterol data before adopting a vegetarian diet from Table 2.1

Average (C5:C28)         Median (C5:C28)           Stdev (C5:C28)              Var (C5:C28)                 GeoMean (C5:C28) Percentile (C5:C28, 0. 1) Percentile (C5:C28, 0.9)

195

145

205

159

244

166

250

236

192

224

238

197

169

158

151

197

180

222

168

168

167

161

178

137

187.7917 179 33.15967 1099.563 185.0761 153.1 237.4

Table A.2 Example of BINOMDIST and POISSON

Example of BINOMDIST

n k p

26

5

0.34

BINOMDIST(5,26,.34, FALSE)

0.048519

26

5

0.34

BINOMDIST(5,26,0.34,TRUE)

0.079197

26

6

0.34

1-BINOMDIST(5,26,0.34,TRUE)

0.920803

Example of POISSON

µ

k

7.4

3

POISSON(3,7.4, FALSE)

0.041282

7.4

3

POISSON(3,7.4,TRUE)

0.063153

7.4

4

1-POISSON(3,7.4,TRUE)

0.936847

POISSON

This function works similarly to BINOMDIST. There are 3 parameters, µ, k and (TRUE/FALSE). Suppose we want to compute Pr(X = 3 µ = 7.4) . This is given by POISSON(3, 7.4, FALSE) = .041. (See Table A.2). If instead we want Pr(X ≤ 3 µ = 7.4) , then we use POISSON(3, 7.4, TRUE) = .063. Note: If we want Pr(X ≥ 4 µ = 7.4) , then we compute 1 – POISSON(3, 7.4, TRUE)= .937. (not 1 – POISSON(4, 7.4, TRUE))

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CHAPTER 5 Continuous Probability Distributions

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There are 4 commands in Excel that are associated with the normal distribution.

NORMDIST

NORMDIST can calculate the pdf and cdf for any normal distribution. The parameters of NORMDIST are NORMDIST(x, mean, sd, TYPE)

Suppose we want to evaluate the pdf at x = 1.0 for a normal distribution with mean = 3 and sd = 2. This is given by

NORMDIST(l.0, 3, 2, FALSE)= pdf of Na3, 22 f distribution evaluated at x = 1.0 = exp2 = 0.121

(See Figure A. 1).

FIGURE A.1

1

x

Suppose we want to evaluate the cdf at x = 1.0 for a normal distribution with mean = 3 and sd = 2. This is given by:

NORMDIST(l.0, 3, 2, TRUE)= cdf of a N(3, 2) distribution evaluated at x = 1.0

= Pr x ≤ 1.0 X ~ Na3, 22 f

= Φ = Φ( −1) = .159

(See Figure A.2).

FIGURE A.2

1

x

NORMINV

NORMINV can calculate percentiles for any normal distribution. The parameters of NORMINV are

NORMINV(p, mean, sd) = the value x such that Pr Xx X ~ Namean, sd2 f = p Suppose we want to calculate the 20th percentile of a Na3, 22 f distribution. This is given by

NORMINV(.2, 3, 2) = the value x such that Pr Xx X ~ Na3, 22 f = 0.2 .

The corresponding x-value is 1.32.

(See Figure A.3).

FIGURE A.3

1.32

x

NORMSDIST

NORMSDIST  can  calculate  the  cdf for  a  standard  normal  distribution.  NORMSDIST  has  a  single parameter x, where

NORMSDIST(x) = PrX x X ~ N(0, 1)

For example, NORMSDIST(1) = Φ(1) = .841 . (See Figure A.4).