Index

NOTE: n after page locator indicates note.

A

Add Rows dialog box 37–38

alternative hypothesis (H1)

defined 184, 208

examples of 186–187

versions of 185

analysis of variance

See ANOVA (analysis of variance)

analysis platforms

See platforms

Analyze menu 53, 87

See also Distribution platform

ANOVA (analysis of variance)

defined 239, 248

Fit Y by X platform and 54

for two groups 244–245

multinomial regression and 304–305

multiple regression and 327

regression analysis and 283–284

tests for three or more means 239–242

B

bar charts 75–78, 98

Bayesian statistics 145, 175

bell-shaped distribution 118

Bernouli random variables 146, 175

bias in sample statistics 12

Binomial Distribution function

about 147

in probability distributions 149–151

inferences about means and 201–202

binomial distributions

defined 146–147, 175

finding quantiles in 150–151

graphing 151

summary measures of 151–152

usage examples 147–150

Binomial Probability function 147–149

Binomial Quantile function 147, 150

binomial regression

defined 294, 306

logistic regression and 294–296

bivariate analysis

correlation analysis and 269–278

defined 312, 350

Density Ellipse and 273–275

Fit Y by X platform and 54, 219, 269

regression analysis and 271, 278–289

Bivariate platform

Density Ellipse and 273–275

regression analysis and 280–289

blue diamond icon 28, 34

bootstrapping

confidence intervals and 202

defined 173, 175

hypothesis testing and 202–203

inferences about median 202–203

sampling distributions and 173–174

bouncing betas problem 352n

Bowley skewness 130

box-and-whisker plot 113, 133n

box plots

defined 113, 133n

outliers 119–120

Bubble Plot dialog box 90

Bubble Plot platform 89

bubble plots 89–90, 98

business analytics 4, 24

business intelligence 4, 24

C

census 10, 24

central limit theorem 167, 175

central tendency, measures of 115, 121

Chart dialog box 75–76, 78

charts for qualitative data

about 75

bar charts 75–78, 98

pie charts 78–79, 98

tree maps 79–81, 98

Chebychev’s Theorem 117–119

chi-square distribution

contingency tables and 257–259

defined 159, 175

examples of 159–161

classical view of probability 145, 175

coefficient of determination 277, 291

coefficient of variation 123, 130

collecting data

See data collection process

color maps 319–321

Column Information dialog box 34

columns

adding 35, 37

adding to reports 72

adding value labels to 46–47

as Data Table panel 33

formatting options for 35–36, 57

hot spots for 35

common cause variability 7–8, 24

Concatenate dialog box 42

concatenating tables

defined 39, 59

process overview 41–43

confidence interval

bootstrapping and 202

defined 183, 208

estimation and 183

margin of error and 183

Confidence Intervals dialog box 194–195

contingency tables

chi-square tests for 257–259

correspondence analysis and 260

defined 91, 98, 251, 267

examples of 255–257

Fit Y by X platform support 91, 219, 252–257, 261–266

graphical presentation of 91–92

two by two 261–266

typical usage 252

Z test and 263–264

continuous probability distributions

about 153

chi-square distribution 159–161, 175

F distribution 161–162, 175

finding probabilities for 157

normal distributions 153–158

Student t-distribution 159, 176

continuous variables

bubble plots and 89–90

defined 19

histograms and 81–83, 106

inferences about means 194

line charts and 84–86

scatter plots and 87–89

stem-and-leaf diagrams and 83–84

Cook’s distance (D) 336–337, 350

copying reports 57–58

correlation

caveats about 277–278

defined 217, 248, 274, 291

hypothesis testing and 276–277

nonparametric 322

pairwise 321–322, 338–339

correlation analysis

about 272

bivariate analysis and 269–270

correlation coefficient 275–278

Density Ellipse and 273–275

multivariate statistics and 312–322

random variables in 271

scatter plots and 272

correlation coefficient 275–278

correlation matrix

Color Maps option and 319–321

defined 315, 350

examples of 315–316

correspondence analysis 260, 267

covariance 276, 291

covariance matrix 321

D

data collection process

about 13–14

classifying data-gathering situations 17–18

experiments and post-hoc studies 17–18, 24

key issues in 15

surveys and observation in 15–18, 24–25

Data Filter dialog box 51–52

data filters

defined 49–50, 59

hot spots for 51

process overview 51–52

data mining 9, 24

Data Table window 33–34

data tables

adding columns 35–37

adding rows 37–38

adding value labels to columns 46–47

combining 39–46

concatenating 39, 41–43, 59

creating 33–34

creating subsets of 49–50

defined 33, 59

entering data into 35–38

filtering 49–52

importing Microsoft Excel data 39–41

joining 39, 43–46, 59

reshaping 48–52

sorting 48–49

data types

continuous variables 19–20

defined 38–39, 59

discrete variables 19–20

qualitative variables 18–19, 75–81

quantitative variables 18–19, 81–86

data warehouse 9, 24

deductive reasoning in statistics 139, 180

degrees of freedom (df) 159

Deming, W. Edwards 6

Density Ellipse 273–275

density functions 153, 175

dependent groups

independent groups and 217–218

Matched Pairs platform and 233–238

qualitative data in 232–238

dependent variable (Y) 217

descriptive statistics

defined 11, 24, 138, 175

inferential statistics and 139

Design of Experiments (DOE) 53

discrete probability distributions

about 146

binomial distributions 146–152, 175

Poisson distribution 152–153, 176

discrete variables 19

dispersion, measures of 115–117

Display Options submenus 58

Distribution dialog box 103, 191–192

Distribution platform

about 53–54, 103

display options 105–106, 123–124

drop-down menu 105

Graphic Analysis panel 106–111

histograms 82, 84

inferences about means 194–197

inferences about one variable 191–193

inferences about proportions 203–207

Moments panel 113–120

More Moments option 120–123

Quantiles panel 111–113

stem-and-leaf diagrams 83

summarizing qualitative data 123–129

summarizing quantitative data 104–123

DOE (Design of Experiments) 53

dummy coding scheme 347–349, 352n

dynamic graphing 110–111

E

empirical rule 117–119

equality sign 185

equivalence testing

additional information 211n

defined 190, 208, 227

examples of 227–228

hypothesis testing and 189–190

estimation

confidence interval and 183

defined 181

finding right sample size 184

in inferential statistics 180–184

in multivariate statistics 318

sampling error and 182–183

expected value 151, 175

experiments

defined 17, 24

examples of 18

post-hoc studies and 218

F

F distribution

defined 161–162, 175

tests for two variances and 225–226

F ratio 242

F test 226

Factor (independent variable) 217

Fermat, Pierre de 144

filtering data

defined 49–50, 59

hot spots for 51

process overview 51–52

filtering data tables 49–52

Fisher’s exact test 263, 267

Fit Model platform

about 54, 323–324

depicted in JMP Starter window 31–32

multiple regression and 312, 322–330

nominal variables and 346–347

regression diagnostics and 333–340

selecting inclusion factors 340–345

stepwise regression 54, 341–345

Fit Y by X dialog box 92–93, 220–221

Fit Y by X platform

See also bivariate analysis

See also contingency tables

See also logistic regression

See also oneway analysis

about 54, 217

accessing 219, 252

comparison of means 243–245

correlation analysis and 272–278

equivalence testing 227

mosaic plots and 92

qualitative data and 252–257

regression analysis and 278–289

scatter plots and 87

tests for three or more means 239–242

tests for three or more medians 246–247

tests for three or more variances 245–246

tests for two means 222–225

tests for two medians 229–232

tests for two variances 226

types of analyses 219–231

formatting

columns 35–36, 57

report tables 55–57

Frequencies reports 55–56

frequency distribution 125, 130

frequency polygons 107

Function dialog box 142

G

G Test (likelihood ratio test) 259, 263

gender discrimination 133

Gossett, William S. 159, 168

Graph Builder dialog box 94

Graph Builder platform

analysis of residuals 333–334

Cook’s Distance 336–337

exploring data with 94–96

line graphs and 85

Graph menu

about 53

Bubble Plot platform 89

Distribution platform and 53

menu options 74–75

Overlay Plot platform 87

Scatterplot Matrix platform 87

Graphic Analysis panel (Distribution platform)

about 106

dynamic graphing 110–111

histograms 106–109

stem-and-leaf diagrams 109–110

graphs for quantitative data

about 81

binomial distributions 151

dynamic graphing 110–111

histograms 81–83, 98, 106–109, 130

line charts 84–86

quantiles and 113

stem-and-leaf diagrams 83–84, 98, 109–110

groups/grouping

See also dependent groups

See also independent groups

ANOVA and t-test for 244–245

qualitative data 216–217

Summary menu command and 70–71

H

histograms

defined 98, 106, 130

display options 123–125

Graphic Analysis panel 106–109

graphical presentation of 81–83

stem-and-leaf diagram comparison 84–85

homogeneity of variances 239, 248

hot spots

defined 28, 59

for columns 35

for data filters 51

for rows 37

table commands 33–34

hypothesis testing

bootstrapping and 202–203

correlation and 276–277

decision outcomes in 185–187

defined 184, 208

examples of 185–188

in inferential statistics 180, 184–190

one-tailed 185

p-values in 188–189

regression analysis and 285–286

tests of equivalence 189–190

two-tailed 185

I

importing Microsoft Excel data 39–41, 63n

INCU example

about 22, 32

bivariate analysis and 270–271

inferential statistics and 181

multivariate statistics and 312

probability and sampling distributions 138

qualitative data and 216, 252

univariate data and 102

visualizing data and 68–69

independent groups

dependent groups and 217–218

equivalence testing 227–228

Fit Y by X platform and 218–221

qualitative data in 218–232

tests for two means 222–225

tests for two medians 228–232

tests for two variances 225–226

independent variable (X) 217

inductive reasoning in statistics 139, 180

inferential statistics

about means 194–197

about medians 199–203

about one variable 191–193

about proportions 203–207

about standard deviations 197–199

about variances 197–199

concept of sampling distributions 162–165

defined 11, 24, 138, 175

descriptive statistics and 139

discovery process and 12–13

estimation in 180–184

hypothesis testing in 180, 184–190

meaning of probability 144–145

populations and samples 138–140

probability distributions 146–162

sampling and 140–144

sampling distributions for common sample statistics 165–174

univariate analysis and 191–193

information technology, changes in 9

interquartile ranges 112, 130

interval scale (measurement)

about 21

bubble plots and 89–90

inferences about means 194

inferences about one variable 191

scatter plots and 87–89

Inverse Prediction dialog box 300–301

blue diamond icon 28, 34

creating data tables 33–39

hot spots for 28, 59

JMP menu 29–30

JMP Starter window 29–32

outline icon 28, 55, 59

reshaping data tables 48–52

tutorials 29

working with data tables 39–47

working with reports 55–58

JMP menu

depicted 29–30

menu structure categories 53

JMP Starter window

about 30

accessing Fit Y by X platform 219, 252

Basic category 30–31, 103

File category 29–30

Graph category 31–32

Model category 31–32

multivariate platforms and 312–313

Tables category 31–32

JMP toolbar 57

Join dialog box 44–45

joining tables

defined 39, 59

process overview 43–46

K

Kelvin scale 26n

kurtosis 120, 122

L

Laplace, Pierre-Simon 145

least squares principle 278, 291

level of significance 186–187, 208

levels (qualitative variables) 218, 248

leverage, measures of 336–338

leverage points 335, 350

likelihood ratio test (G Test) 259, 263

line charts 84–86

linear regression, assumptions of 279–280

log odds (logit) 295, 306

logistic regression

binomial regression and 294–296

Fit Y by X platform and 219, 293, 296–301

inverse prediction 300–301

multinomial regression and 302–305

logit (log odds) 295, 306

lower-tailed tests 185

M

Marascuilo tests 259, 267

margin of error 183, 209

Matched Pairs dialog box 235–236

Matched Pairs platform 54, 233–238

mean

as measure of central tendency 115

comparison of means 243–245

defined 114, 130

inferences about 194–197

sampling distributions for 166–170

tests for three or more means 238–245

tests for two means 222–225

mean square 242, 248

measurement, scales of 20–21

See also specific scales of measurement

measures of central tendency 115, 121

measures of dispersion or variability 115–117

measures of shapes 120–123

median

as measure of central tendency 115

bootstrapping inference about 202–203

defined 112, 130

inferences about 199–203

sampling distributions for 172–173

sign test for 199–202

tests for three or more medians 246–247

tests for two medians 228–232

Microsoft Excel, importing data from 39–41, 63n

mode

as measure of central tendency 115

defined 115, 131

modeling types 38–39, 59

moment skewness 121, 131

Moments panel (Distribution platform)

about 113–114

identifying outliers 119–120

measures of central tendency 115

measures of dispersion or variability 115–117

standard deviation uses 117–119

Moments reports 55–56

mosaic plots

contingency tables and 254, 261

defined 98, 124, 131

graphical presentation of 92–93

multicollinearity

defined 338, 350

regression analysis and 338–340

multinomial regression

defined 294, 306

Fit Y by X platform and 302–305

multiple comparison tests 243–245, 249

multiple regression

ANOVA and 327

Fit Model platform and 312, 322–330

regression coefficients in 328

regression diagnostics 330–340

standardized regression coefficients 329–330

Multivariate dialog box 314–315

Multivariate platform

Color Maps option 319–321

correlation analysis and 313–322

Covariance Matrix option 321

estimation method 318

Nonparametric Correlations option 322

Pairwise Correlations option 321–322

multivariate statistics

correlation analysis and 313–322

defined 312, 350

Fit Model platform and 54, 312–313, 322–330

JMP platforms 312–313

multiple regression and 322–330

nominal variables in 345–349

regression diagnostics 330–340

selecting inclusion factors 340–345

N

New Data Table option (JMP Starter) 33

nominal scale (measurement)

bar charts and 75–78

contingency tables and 91–92

defined 20

inferences about one variable 191

mosaic plots and 92–93

pie charts and 78–79

qualitative data and 216

regression models and 345–349

tree maps and 79–81

nonparametric correlations 322

nonparametric statistics

defined 228, 249

tests for two medians 228–232

nonprobability sampling 140, 175

nonsampling error

defined 12, 24, 182, 209

sampling error and 12, 182–183

Normal Density function 155

normal distribution

defined 153, 175

finding probabilities for 157

finding quantiles in 158

standard 154, 160, 176

usage examples 154–157

Normal Distribution function

about 155

in hypothesis testing 189

in probability distributions 156–157

in sampling distributions 169

Normal Quantile function

about 155

in hypothesis testing 188

in probability distributions 158

in sampling distributions 169

null hypothesis (H0)

defined 184, 209

equality sign in 185

examples of 185–188

Type I error and 186

Type II error and 186

O

observations

defined 15–17, 24

examples of 18

odds, defined 295, 306

one-tailed hypothesis tests 185

oneway analysis

ANOVA example 244–245

equivalence testing 227–228

Fit Y by X platform and 219–221

tests for three or more means 239–242

tests for three or more medians 246–247

tests for two means 222–225

tests for two medians 228–232

tests for two variances 225–226

Open Data File dialog box 40–41

ordinal scale (measurement)

about 20–21

bar charts and 75–78

contingency tables and 91–92

inferences about one variable 191

mosaic plots and 92–93

pie charts and 78–79

tree maps and 79–81

organizations, process view of 6–7

outlier box plots 113

outliers

defined 113, 131, 335, 350

identifying 119–120

regression analysis and 287–289, 335–338

outline icon 28, 55, 59

Overlay Plot dialog box 86–87

Overlay Plot platform 85, 87–88

P

p-values

defined 188, 209

in hypothesis testing 188–189

pairwise correlations 321–322, 338–339

parameters

See population parameters

Pascal, Blaise 144

Pearson, Karl 133n

Pearson chi-square test 259

Pearson skewness 122, 131

pie charts 78–79, 98

platforms

defined 53, 59

JMP supported 53–54

multivariate analysis and 312–313

performing further analysis 58

Poisson distribution 152–153, 176

Poisson Distribution function 152

Poisson Probability function 152

Poisson Quantile function 152

population

defined 10, 24, 138, 176

of values 163–164

samples and 138–139

standard deviation and 166–170

population parameters

defined 10, 24, 140, 176

estimation and 181

sample statistics and 140

post-hoc studies

defined 17, 24

examples of 18

experiments and 218

power, defined 186, 209

primary data

collecting 15

defined 13, 25

principle of least squares 278, 291

printing

reference cards 29

reports 57–58

probability

classical view of 145, 175

defined 144–145

relative frequency view of 145, 176

subjective view of 145, 176

probability distributions

continuous 153–162, 175–176

defined 146, 176

discrete 146–153

random variables and 146

sampling distributions as 165

probability sampling

defined 140, 176

inferential statistics and 144

simple random samples 140–144

process view of organizations 6–7

proportions

defined 125, 131

finding sample size for 206–207

inferences about 203–207

risk difference for 264–267

sampling distributions for 171–172

tests of 252

pure error 286, 291

Q

qualitative data

charts for 75–81

contingency tables and 91–92

correspondence analysis and 260

defined 18–19, 216

Fit Y by X platform and 252–257

grouping 216–217

in dependent groups 232–238

in independent groups 218–232

levels of 218, 248

mosaic plots and 92–93

summary measures for 123–129

tests for three or more means 238–245

tests for three or more medians 246–247

tests for three or more variances 245–246

tests of independence 252

tests of proportions 252

quantiles

defined 111, 131

finding in binomial distributions 150–151

finding in normal distributions 158

graphs and 113

quartiles and 111–112

Quantiles panel (Distribution platform) 111–113

Quantiles reports 55–56

quantitative data

See also bivariate analysis

See also graphs for quantitative data

defined 18–19

summarizing 104–123

quartiles 111–112, 131

R

Random Uniform function 141

random variables

Bernouli 146, 175

defined 146, 176

in correlation analysis 271

in regression analysis 271

probability distributions and 146

ratio scale (measurement)

about 21

bubble plots and 89–90

inferences about means 194

inferences about one variable 191

scatter plots and 87–89

reference cards, printing 29

regression analysis

See also specific types of regression

about 278, 280–282

ANOVA and 283–284

assumptions of linear regression 279–280

correlation analysis versus 271–278

hypothesis testing and 285–286

lack of fit and 286–287

multicollinearity and 338–340

nominal variables in 345–349

outliers and 287–289, 335–338

parameter estimates 284–285

random variables in 271

regression diagnostics 330–340

summary of fit and 282

regression coefficients

defined 328, 350

standardized 329–330, 350

relationships between variables 87–89

relative frequency view of probability 145, 176

reports

about 55

adding columns to 72

copying 57–58

Display Options submenus 58

formatting report tables 55–57

printing 57–58

resampling 173, 176

reshaping data tables

by creating subsets 49–50

by filtering 49–52

by sorting 48–49

residuals

analysis of 330–334

defined 278, 291

studentized 333

Response (dependent variable) 217

risk difference 264–267

root mean square error 282, 291

rows

adding 37–38

as Data Table panel 33

hot spots for 37

S

sample

defined 10, 25, 138, 176

population and 138–139

sample size

central limit theorem and 167

defined 114

degrees of freedom and 159

finding 184

finding for proportions 206–207

sample statistic

bias in 12

defined 10, 25, 140, 176

estimation and 181

population of values for 163–164

population parameters and 140

sampling distributions and 162, 165–174

t-test statistic and 224

sampling

See probability sampling

sampling distributions

as population of values 163–164

as probability distribution 165

bootstrapping and 173–174

building 162–163

central limit theorem and 167

defined 139, 162, 176

for common sample statistics 165–174

for standard deviation 170

for the mean 166–170

for the median 172–173

for the proportion 171–172

for variance 170

in inferential statistics 180

sampling error

defined 11–12, 25, 182, 209

nonsampling error and 12, 182–183

sampling frame 141, 176

scales of measurement 20–21

See also specific scales of measurement

scatter plots

correlation analysis and 272

defined 98

Density Ellipse examples 273–275

graphical presentation of 87–89

Scatterplot Matrix platform 87, 317–318

scripts

as Data Table panel 33

for medians utilizing bootstrapping 202

secondary data

advantages/disadvantages of 14–15

defined 13, 25

principal sources of 14

selection tool (JMP toolbar) 57

shadowgrams 107, 131

shapes, measures of 120–123

Shneiderman, Bob 100n

sign test for median 199–202

simple random sample 140, 176

Six Sigma movement 7

skewness 120–121, 131

slope, defined 281, 291

Sort dialog box 48

sorting data tables 48–49

Spearman rank correlations 322, 350

special cause variability 7–8, 25

Split Column dialog box 233–234

Split command 233

Stack command 233

standard deviation

Chebychev’s Theorem and 117–119

customer survey data and 119

defined 114, 116–117, 131

empirical rule and 117–119

inferences about 197–199

population 166–170

sampling distributions for 170

standard scores and 117

standard error

defined 166, 176

t-test statistic and 224

standard error of the estimate 282, 291

standard normal distribution 154, 160, 176

standard scores 117

standardized regression coefficients 329–330, 350

statistical inference

See inferential statistics

statistical significance

defined 221, 249

leverage and 336

statistical tables

about 69

creating with Summary menu command 69–72

creating with Tabulate command 72–74

statistical thinking 7, 25

statistics

data collection process 13–18

deductive reasoning in 139, 180

defined 5, 25

important concepts in 10–13

inductive reasoning in 139, 180

modern view of 6–10

reasons for studying 4–5

sampling in 140–144

scales of measurement in 20–21

traditional view of 5–6

types of data in 18–21

stem-and-leaf diagrams

defined 98

Graphic Analysis panel 109–110

graphical presentation of 83–84

histogram comparison 84–85

Stepwise dialog box 341–342

stepwise regression

defined 341, 350

Fit Model platform and 54, 341–345

Stevens, S.S. 20

Student t-distribution

comparison of means and 243

defined 159–160, 176

sampling distribution and 168

studentized residuals 333, 350

subjective view of probability 145, 176

Subset dialog box 49–50

subsets of data tables 49–50

summary measures

defined 114, 131

Distribution platform and 53, 103

for qualitative data 123–129

for quantitative data 104–123

Moments panel and 114

of binomial distributions 151–152

Summary menu command

adding columns to reports 72

contingency tables and 91

creating summary tables 69–71

grouping statistics in 70–71

Summary Table dialog box 70

surveys

defined 15–17, 25

examples of 18

standard deviation and 119

T

t-test

about 224–225

for two groups 244–245

Table Formatting menu 57

Table Style submenu 55, 57

tables

See data tables

Tabulate command

contingency tables and 91

creating tables with 72–74

Graph Builder and 94

Tabulate dialog box 72, 91–92

Test Mean dialog box 195–196

Test Standard Deviation dialog box 198

test statistic

defined 166, 176

for chi-square tests 257–258

for Wald test 298

for Z tests 263

tests for three or more means 238–245

tests for two means 222–225

tests for two medians 228–232

tests for two variances 225–226

tests of independence 252

tests of proportions 252

Time Series platform 31–32

Tip of the Day window 63n

TOST (two one-sided tests) 190, 209

Tree Map dialog box 79–80

tree maps 79–81, 98

Tukey, John 83

tutorials, JMP 29

two one-sided tests (TOST) 190, 209

two-tailed hypothesis tests 185

Type I error 186, 208

Type II error 186

types of data

See data types

U

unbiased estimator 181, 209

univariate analysis

defined 191, 209, 312, 350

Distribution platform and 53, 103

inferential statistics and 191–193

summarizing qualitative data 123–129

summarizing quantitative data 104–123

upper-tailed tests 185

V

van der Waerden test 229

variability

analysis of residuals 330–334

common cause 7–8, 24

measures of 115–117

special cause 7–8, 25

variables

See columns

variance inflation factors (VIF) 338–339, 350

variances

defined 116–117, 131

homogeneity of 239, 248

inferences about 197–199

sampling distributions for 170

tests for three or more variances 245–246

tests for two variances 225–226

VIF (variance inflation factors) 338–339, 350

W

Wald test 298

Wilcoxon test 229–231

X

X (independent variable) 217

Y

Y (dependent variable) 217

Y intercept 281, 291

Z

Z test 263–264