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Statistical Analysis with Excel For Dummies 5th edition [Pehme köide]

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  • Formaat: Paperback / softback, 576 pages, kõrgus x laius x paksus: 231x185x36 mm, kaal: 726 g
  • Ilmumisaeg: 21-Mar-2022
  • Kirjastus: For Dummies
  • ISBN-10: 1119844541
  • ISBN-13: 9781119844549
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Statistical Analysis with Excel For Dummies 5th editionSuurem pilt
  • Formaat: Paperback / softback, 576 pages, kõrgus x laius x paksus: 231x185x36 mm, kaal: 726 g
  • Ilmumisaeg: 21-Mar-2022
  • Kirjastus: For Dummies
  • ISBN-10: 1119844541
  • ISBN-13: 9781119844549
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781119844549.html
Märksõnad:
Become a stats superstar by using Excel to reveal the powerful secrets of statistics. Original. Illustrations. Appendix. Index.

Become a stats superstar by using Excel to reveal the powerful secrets of statistics 

Microsoft Excel offers numerous possibilities for statistical analysis—and you don’t have to be a math wizard to unlock them. In Statistical Analysis with Excel For Dummies, fully updated for the 2021 version of Excel, you’ll hit the ground running with straightforward techniques and practical guidance to unlock the power of statistics in Excel.

Bypass unnecessary jargon and skip right to mastering formulas, functions, charts, probabilities, distributions, and correlations. Written for professionals and students without a background in statistics or math, you’ll learn to create, interpret, and translate statistics—and have fun doing it! 

In this book you’ll find out how to: 

  • Understand, describe, and summarize any kind of data, from sports stats to sales figures 
  • Confidently draw conclusions from your analyses, make accurate predictions, and calculate correlations 
  • Model the probabilities of future outcomes based on past data 
  • Perform statistical analysis on any platform: Windows, Mac, or iPad 
  • Access additional resources and practice templates through Dummies.com 

For anyone who’s ever wanted to unleash the full potential of statistical analysis in Excel—and impress your colleagues or classmates along the way—Statistical Analysis with Excel For Dummies walks you through the foundational concepts of analyzing statistics and the step-by-step methods you use to apply them.   

Introduction 1(6)
About This Book
2(1)
What's New in This Edition
2(1)
What's New in Excel (Microsoft 365)
3(1)
Foolish Assumptions
3(1)
Icons Used in This Book
4(1)
Where to Go from Here
5(1)
Beyond This Book
5(2)
Part 1: Getting Started With Statistical Analysis With Excel: A Marriage Made In Heaven 7(56)
Chapter 1 Evaluating Data in the Real World
9(20)
The Statistical (and Related) Notions You Just Have to Know
9(5)
Samples and populations
10(1)
Variables: Dependent and independent
11(1)
Types of data
12(1)
A little probability
13(1)
Inferential Statistics: Testing Hypotheses
14(4)
Null and alternative hypotheses
15(1)
Two types of error
16(2)
Some Excel Fundamentals
18(11)
Autofilling cells
22(3)
Referencing cells
25(4)
Chapter 2 Understanding Excel's Statistical Capabilities
29(34)
Getting Started
30(2)
Setting Up for Statistics
32(18)
Worksheet functions
32(4)
Quickly accessing statistical functions
36(2)
Array functions
38(3)
What's in a name? An array of possibilities
41(9)
Creating Your Own Array Formulas
50(8)
Using data analysis tools
51(5)
Additional data analysis tool packages
56(2)
Accessing Commonly Used Functions
58(1)
The New Analyze Data Tool
59(1)
Data from Pictures'
60(3)
Part 2: Describing Data 63(110)
Chapter 3 Show-and-Tell: Graphing Data
65(26)
Why Use Graphs?
65(2)
Examining Some Fundamentals
67(1)
Gauging Excel's Graphics (Chartics?) Capabilities
68(1)
Becoming a Columnist
69(4)
Stacking the Columns
73(1)
Slicing the Pie
74(3)
A word from the wise
76(1)
Drawing the Line
77(3)
Adding a Spark
80(2)
Passing the Bar
82(2)
The Plot Thickens
84(4)
Finding Another Use for the Scatter Chart
88(3)
Chapter 4 Finding Your Center
91(16)
Means: The Lore of Averages
91(11)
Calculating the mean
92(1)
AVERAGE and AVERAGEA
93(2)
AVERAGEIF and AVERAGEIFS
95(4)
TRIMMEAN
99(1)
Other means to an end
100(2)
Medians: Caught in the Middle
102(2)
Finding the median
102(1)
MEDIAN
103(1)
Statistics a la Mode
104(3)
Finding the mode
104(1)
MODE.SNGL and MODE.MULT
104(3)
Chapter 5 Deviating from the Average
107(18)
Measuring Variation
108(6)
Averaging squared deviations: Variance and how to calculate it
108(3)
VAR.P and VARPA
111(2)
Sample variance
113(1)
VAR.S and VARA
114(1)
Back to the Roots: Standard Deviation
114(7)
Population standard deviation
115(1)
STDEV.P and STDEVPA
115(1)
Sample standard deviation
116(1)
STDEV.S and STDEVA
116(1)
The missing functions: STDEVIF and STDEVIFS
117(4)
Related Functions
121(4)
DEVSQ
121(1)
Average deviation
122(1)
AVEDEV
123(2)
Chapter 6 Meeting Standards and Standings
125(16)
Catching Some Z's
126(5)
Characteristics of z-scores
126(1)
Bonds versus the Bambino
127(1)
Exam scores
128(1)
STANDARDIZE
128(3)
Where Do You Stand?
131(10)
RANK.EQ and RANK.AVG
131(2)
LARGE and SMALL
133(1)
PERCENTILE.INC and PERCENTILE.EXC
134(3)
PERCENTRANK.INC and PERCENTRANK.EXC
137(1)
Data analysis tool: Rank and Percentile
138(3)
Chapter 7 Summarizing It All
141(20)
Counting Out
141(3)
COUNT, COUNTA, COUNTBLANK, COUNTIF, COUNTIFS
141(3)
The Long and Short of It
144(1)
MAX, MAXA, MIN, and MINA
144(1)
Getting Esoteric
145(5)
SKEW and SKEW.P
146(2)
KURT
148(2)
Tuning In the Frequency
150(4)
FREQUENCY
150(2)
Data analysis tool: Histogram
152(2)
Can You Give Me a Description?
154(2)
Data analysis tool: Descriptive Statistics
154(2)
Be Quick About It
156(3)
Instant Statistics
159(2)
Chapter 8 What's Normal?
161(12)
Hitting the Curve
161(7)
Digging deeper
162(1)
Parameters of a normal distribution
163(2)
NORM.DIST
165(2)
NORM.INV
167(1)
A Distinguished Member of the Family
168(3)
NORM.S.DIST
169(1)
NORM.S.INV
170(1)
PHI and GAUSS
170(1)
Graphing a Standard Normal Distribution
171(2)
Part 3: Drawing Conclusions From Data 173(220)
Chapter 9 The Confidence Game: Estimation
175(14)
Understanding Sampling Distributions
176(1)
An EXTREMELY Important Idea: The Central Limit Theorem
177(6)
(Approximately) simulating the Central Limit Theorem
178(5)
The Limits of Confidence
183(4)
Finding confidence limits for a mean
183(3)
CONFIDENCE.NORM
186(1)
Fit to a t
187(2)
CONFIDENCE.T
188(1)
Chapter 10 One-Sample Hypothesis Testing
189(22)
Hypotheses, Tests, and Errors
190(1)
Hypothesis Tests and Sampling Distributions
191(2)
Catching Some Z's Again
193(4)
Z.TEST
196(1)
t for One
197(4)
T.DIST, T.DIST.RT, and T.DIST.2T
198(2)
T.INV and T.INV.2T
200(1)
Visualizing a t-Distribution
201(2)
Testing a Variance
203(5)
CHISQ.DIST and CHISQ.DIST.RT
205(1)
CHISQ.INV and CHISQ.INV.RT
206(2)
Visualizing a Chi-Square Distribution
208(3)
Chapter 11 Two-Sample Hypothesis Testing
211(36)
Hypotheses Built for Two
211(1)
Sampling Distributions Revisited
212(7)
Applying the Central Limit Theorem
213(2)
Z's once more
215(1)
Data analysis tool: z-Test: Two Sample for Means
216(3)
t for Two
219(8)
Like peas in a pod: Equal variances
220(1)
Like p's and q's: Unequal variances
221(1)
T.TEST
222(1)
Data analysis tool: t-Test: Two Sample
223(4)
A Matched Set: Hypothesis Testing for Paired Samples
227(8)
T.TEST for matched samples
228(2)
Data analysis tool: t-Test: Paired Two Sample for Means
230(2)
t-tests on the iPad with StatPlus
232(3)
Testing Two Variances
235(9)
Using F in conjunction with t
237(1)
F.TEST
238(2)
F.DIST and F.DIST.RT
240(1)
F.INV and F.INV.RT
241(1)
Data analysis tool: F-test: Two Sample for Variances
242(2)
Visualizing the F-Distribution
244(3)
Chapter 12 Testing More Than Two Samples
247(34)
Testing More than Two
247(15)
A thorny problem
248(1)
A solution
249(4)
Meaningful relationships
253(1)
After the F-test
254(4)
Data analysis tool: Anova: Single Factor
258(2)
Comparing the means
260(2)
Another Kind of Hypothesis, Another Kind of Test
262(10)
Working with repeated measures ANOVA
262(2)
Getting trendy
264(4)
Data analysis tool: Anova: Two-Factor Without Replication
268(3)
Analyzing trend
271(1)
ANOVA on the iPad
272(2)
ANOVA on the iPad: Another Way
274(3)
Repeated Measures ANOVA on the iPad
277(4)
Chapter 13 Slightly More Complicated Testing
281(22)
Cracking the Combinations
281(5)
Breaking down the variances
282(2)
Data analysis tool: Anova: Two-Factor Without Replication
284(2)
Cracking the Combinations Again
286(6)
Rows and columns
286(1)
Interactions
287(1)
The analysis
288(1)
Data analysis tool: Anova: Two-Factor With Replication
289(3)
Two Kinds of Variables - at Once
292(1)
Using Excel with a Mixed Design
293(5)
Graphing the Results
298(2)
After the ANOVA
300(1)
Two-Factor ANOVA on the iPad
300(3)
Chapter 14 Regression: Linear and Multiple
303(38)
The Plot of Scatter
303(2)
Graphing a line
305(2)
Regression: What a Line!
307(10)
Using regression for forecasting
309(1)
Variation around the regression line
309(2)
Testing hypotheses about regression
311(6)
Worksheet Functions for Regression
317(8)
SLOPE, INTERCEPT, STEYX
318(1)
FORECAST. LI N EAR
319(1)
Array function: TREND
319(4)
Array function: LINEST
323(2)
Data Analysis Tool: Regression
325(5)
Working with tabled output
327(2)
Opting for graphical output
329(1)
Juggling Many Relationships at Once: Multiple Regression
330(1)
Excel Tools for Multiple Regression
331(7)
TREND revisited
331(2)
LINEST revisited
333(3)
Regression data analysis tool revisited
336(2)
Regression Analysis on the iPad
338(3)
Chapter 15 Correlation: The Rise and Fall of Relationships
341(22)
Scatterplots Again
341(1)
Understanding Correlation
342(3)
Correlation and Regression
345(2)
Testing Hypotheses about Correlation
347(3)
Is a correlation coefficient greater than zero?
348(1)
Do two correlation coefficients differ?
349(1)
Worksheet Functions for Correlation
350(3)
CORREL and PEARSON
350(1)
RSQ
351(1)
COVARIANCE.P and COVARIANCE.S
352(1)
Data Analysis Tool: Correlation
353(5)
Tabled output
354(1)
Multiple correlation
355(1)
Partial correlation
356(1)
Semipartial correlation
357(1)
Data Analysis Tool: Covariance
358(1)
Using Excel to Test Hypotheses about Correlation
358(2)
Worksheet functions: FISHER, FISHERINV
359(1)
Correlation Analysis on the iPad
360(3)
Chapter 16 It's About Time
363(16)
A Series and Its Components
363(1)
A Moving Experience
364(4)
Lining up the trend
365(1)
Data analysis tool: Moving Average
365(3)
How to Be a Smoothie, Exponentially
368(1)
One-Click Forecasting
369(5)
Working with Time Series on the iPad
374(5)
Chapter 17 Nonparametric Statistics
379(14)
Independent Samples
380(3)
Two samples: Mann-Whitney U test
380(2)
More than two samples: Kruskal-Wallis one-way ANOVA
382(1)
Matched Samples
383(6)
Two samples: Wilcoxon matched-pairs signed ranks
384(2)
More than two samples: Friedman two-way ANOVA
386(1)
More than two samples: Cochran's Q
387(2)
Correlation: Spearman's rs
389(2)
A Heads-Up
391(2)
Part 4: Probability 393(72)
Chapter 18 Introducing Probability
395(24)
What Is Probability?
395(2)
Experiments, trials, events, and sample spaces
396(1)
Sample spaces and probability
396(1)
Compound Events
397(2)
Union and intersection
397(1)
Intersection, again
398(1)
Conditional Probability
399(1)
Working with the probabilities
400(1)
The foundation of hypothesis testing
400(1)
Large Sample Spaces
400(3)
Permutations
401(1)
Combinations
402(1)
Worksheet Functions
403(2)
FACT
403(1)
PERMUT and PERMUTIONA
403(1)
COMBIN and COMBINA
404(1)
Random Variables: Discrete and Continuous
405(1)
Probability Distributions and Density Functions
405(2)
The Binomial Distribution
407(2)
Worksheet Functions
409(3)
BINOM.DIST and BINOM.DIST.RANGE
409(2)
NEGBINOM.DIST
411(1)
Hypothesis Testing with the Binomial Distribution
412(3)
BINOM.INV
413(1)
More on hypothesis testing
414(1)
The Hypergeometric Distribution
415(4)
HYPGEOM.DIST
416(3)
Chapter 19 More on Probability
419(14)
Discovering Beta
419(5)
BETA.DIST
421(2)
BETA.I NV
423(1)
Poisson
424(3)
POISSON.DIST
425(2)
Working with Gamma
427(4)
The gamma function and GAMMA
427(1)
The gamma distribution and GAMMA.DIST
428(2)
GAMMA.INV
430(1)
Exponential
431(2)
EXPON.DIST
431(2)
Chapter 20 Using Probability: Modeling and Simulation
433(24)
Modeling a Distribution
434(10)
Plunging into the Poisson distribution
434(1)
Visualizing the Poisson distribution
435(1)
Working with the Poisson distribution
436(1)
Using POISSON.DIST again
437(1)
Testing the model's fit
437(3)
A word about CHISQ.TEST
440(1)
Playing ball with a model
441(3)
A Simulating Discussion
444(13)
Taking a chance: The Monte Carlo method
444(1)
Loading the dice
444(1)
Data analysis tool: Random Number Generation
445(3)
Simulating the Central limit Theorem
448(4)
Simulating a business
452(5)
Chapter 21 Estimating Probability: Logistic Regression
457(8)
Working Your Way Through Logistic Regression
458(2)
Mining with XLMiner
460(5)
Part 5: The Part Of Tens 465(36)
Chapter 22 Ten (12, Actually) Statistical and Graphical Tips and Traps
467(8)
Significant Doesn't Always Mean Important
467(1)
Trying to Not Reject a Null Hypothesis Has a Number of Implications
468(1)
Regression Isn't Always Linear
468(1)
Extrapolating Beyond a Sample Scatterplot Is a Bad Idea
469(1)
Examine the Variability Around a Regression Line
469(1)
A Sample Can Be Too Large
470(1)
Consumers: Know Your Axes
470(1)
Graphing a Categorical Variable as a Quantitative Variable Is Just Plain Wrong
471(1)
Whenever Appropriate, Include Variability in Your Graph
472(1)
Be Careful When Relating Statistics Textbook Concepts to Excel
472(1)
It's Always a Good Idea to Use Named Ranges in Excel
472(1)
Statistical Analysis with Excel on the iPad Is Pretty Good!
473(2)
Chapter 23 Ten Topics (Thirteen, Actually) That Just Don't Fit Elsewhere
475(26)
Graphing the Standard Error of the Mean
475(4)
Probabilities and Distributions
479(1)
PROB
479(1)
WEIBULL.DIST
479(1)
Drawing Samples
480(1)
Testing Independence: The True Use of CHISQ.TEST
481(17)
Logarithmica Esoterica
484(1)
What is a logarithm?
484(2)
What is e?
486(3)
LOGNORM.DIST
489(1)
LOGNORM.INV
490(1)
Array Function: LOGEST
491(3)
Array Function: GROWTH
494(3)
The logs of Gamma
497(1)
Sorting Data
498(3)
Part 6: Appendices 501(44)
Appendix A: When Your Data Live Elsewhere
503(4)
Appendix B: Tips for Teachers (and Learners)
507(8)
Augmenting Analyses Is a Good Thing
507(5)
Understanding ANOVA
508(2)
Revisiting regression
510(2)
Simulating Data Is Also a Good Thing
512(2)
When All You Have Is a Graph
514(1)
Appendix C: More on Excel Graphics
515(14)
Tasting the Bubbly
515(1)
Taking Stock
516(2)
Scratching the Surface
518(1)
On the Radar
519(1)
Growing a Treemap and Bursting Some Sun
520(1)
Building a Histogram
521(1)
Ordering Columns: Pareto
522(1)
Of Boxes and Whiskers
523(1)
3D Maps
524(3)
Filled Maps
527(2)
Appendix D: The Analysis of Covariance
529(16)
Covariance: A Closer Look
529(1)
Why You Analyze Covariance
530(1)
How You Analyze Covariance
531(1)
ANCOVA in Excel
532(10)
Method 1: ANOVA
533(4)
Method 2: Regression
537(3)
After the ANCOVA
540(2)
And One More Thing
542(3)
Index 545
Joseph Schmuller works on the Digital & Enterprise Architecture Team at Availity. He has taught statistics at the undergraduate and graduate levels. He has created and delivered courses for LinkedIn Learning, and he is the author of all previous editions of Statistical Analysis with Excel For Dummies.