Statistical Analysis with Excel For Dummies, 5th Edition
- Length: 576 pages
- Edition: 5
- Language: English
- Publisher: For Dummies
- Publication Date: 2022-01-19
- ISBN-10: 1119844541
- ISBN-13: 9781119844549
- Sales Rank: #700947 (See Top 100 Books)
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.
Title Page Copyright Page Table of Contents Introduction About This Book What’s New in This Edition What’s New in Excel (Microsoft 365) Foolish Assumptions Icons Used in This Book Where to Go from Here Beyond This Book Part 1 Getting Started with Statistical Analysis with Excel: A Marriage Made in Heaven Chapter 1 Evaluating Data in the Real World The Statistical (and Related) Notions You Just Have to Know Samples and populations Variables: Dependent and independent Types of data A little probability Inferential Statistics: Testing Hypotheses Null and alternative hypotheses Two types of error Some Excel Fundamentals Autofilling cells Referencing cells Chapter 2 Understanding Excel’s Statistical Capabilities Getting Started Setting Up for Statistics Worksheet functions Quickly accessing statistical functions Array functions What’s in a name? An array of possibilities Creating Your Own Array Formulas Using data analysis tools Additional data analysis tool packages Accessing Commonly Used Functions The New Analyze Data Tool Data from Pictures! Part 2 Describing Data Chapter 3 Show-and-Tell: Graphing Data Why Use Graphs? Examining Some Fundamentals Gauging Excel’s Graphics (Chartics?) Capabilities Becoming a Columnist Stacking the Columns Slicing the Pie A word from the wise Drawing the Line Adding a Spark Passing the Bar The Plot Thickens Finding Another Use for the Scatter Chart Chapter 4 Finding Your Center Means: The Lore of Averages Calculating the mean AVERAGE and AVERAGEA AVERAGEIF and AVERAGEIFS TRIMMEAN Other means to an end Medians: Caught in the Middle Finding the median MEDIAN Statistics à la Mode Finding the mode MODE.SNGL and MODE.MULT Chapter 5 Deviating from the Average Measuring Variation Averaging squared deviations: Variance and how to calculate it VAR.P and VARPA Sample variance VAR.S and VARA Back to the Roots: Standard Deviation Population standard deviation STDEV.P and STDEVPA Sample standard deviation STDEV.S and STDEVA The missing functions: STDEVIF and STDEVIFS Related Functions DEVSQ Average deviation AVEDEV Chapter 6 Meeting Standards and Standings Catching Some Z’s Characteristics of z-scores Bonds versus the Bambino Exam scores STANDARDIZE Where Do You Stand? RANK.EQ and RANK.AVG LARGE and SMALL PERCENTILE.INC and PERCENTILE.EXC PERCENTRANK.INC and PERCENTRANK.EXC Data analysis tool: Rank and Percentile Chapter 7 Summarizing It All Counting Out COUNT, COUNTA, COUNTBLANK, COUNTIF, COUNTIFS The Long and Short of It MAX, MAXA, MIN, and MINA Getting Esoteric SKEW and SKEW.P KURT Tuning In the Frequency FREQUENCY Data analysis tool: Histogram Can You Give Me a Description? Data analysis tool: Descriptive Statistics Be Quick About It! Instant Statistics Chapter 8 What’s Normal? Hitting the Curve Digging deeper Parameters of a normal distribution NORM.DIST NORM.INV A Distinguished Member of the Family NORM.S.DIST NORM.S.INV PHI and GAUSS Graphing a Standard Normal Distribution Part 3 Drawing Conclusions from Data Chapter 9 The Confidence Game: Estimation Understanding Sampling Distributions An EXTREMELY Important Idea: The Central Limit Theorem (Approximately) simulating the Central Limit Theorem The Limits of Confidence Finding confidence limits for a mean CONFIDENCE.NORM Fit to a t CONFIDENCE.T Chapter 10 One-Sample Hypothesis Testing Hypotheses, Tests, and Errors Hypothesis Tests and Sampling Distributions Catching Some Z’s Again Z.TEST t for One T.DIST, T.DIST.RT, and T.DIST.2T T.INV and T.INV.2T Visualizing a t-Distribution Testing a Variance CHISQ.DIST and CHISQ.DIST.RT CHISQ.INV and CHISQ.INV.RT Visualizing a Chi-Square Distribution Chapter 11 Two-Sample Hypothesis Testing Hypotheses Built for Two Sampling Distributions Revisited Applying the Central Limit Theorem Z’s once more Data analysis tool: z-Test: Two Sample for Means t for Two Like peas in a pod: Equal variances Like p’s and q’s: Unequal variances T.TEST Data analysis tool: t-Test: Two Sample A Matched Set: Hypothesis Testing for Paired Samples T.TEST for matched samples Data analysis tool: t-Test: Paired Two Sample for Means t-tests on the iPad with StatPlus Testing Two Variances Using F in conjunction with t F.TEST F.DIST and F.DIST.RT F.INV and F.INV.RT Data analysis tool: F-test: Two Sample for Variances Visualizing the F-Distribution Chapter 12 Testing More Than Two Samples Testing More than Two A thorny problem A solution Meaningful relationships After the F-test Data analysis tool: Anova: Single Factor Comparing the means Another Kind of Hypothesis, Another Kind of Test Working with repeated measures ANOVA Getting trendy Data analysis tool: Anova: Two-Factor Without Replication Analyzing trend ANOVA on the iPad ANOVA on the iPad: Another Way Repeated Measures ANOVA on the iPad Chapter 13 Slightly More Complicated Testing Cracking the Combinations Breaking down the variances Data analysis tool: Anova: Two-Factor Without Replication Cracking the Combinations Again Rows and columns Interactions The analysis Data analysis tool: Anova: Two-Factor With Replication Two Kinds of Variables — at Once Using Excel with a Mixed Design Graphing the Results After the ANOVA Two-Factor ANOVA on the iPad Chapter 14 Regression: Linear and Multiple The Plot of Scatter Graphing a line Regression: What a Line! Using regression for forecasting Variation around the regression line Testing hypotheses about regression Worksheet Functions for Regression SLOPE, INTERCEPT, STEYX FORECAST.LINEAR Array function: TREND Array function: LINEST Data Analysis Tool: Regression Working with tabled output Opting for graphical output Juggling Many Relationships at Once: Multiple Regression Excel Tools for Multiple Regression TREND revisited LINEST revisited Regression data analysis tool revisited Regression Analysis on the iPad Chapter 15 Correlation: The Rise and Fall of Relationships Scatterplots Again Understanding Correlation Correlation and Regression Testing Hypotheses about Correlation Is a correlation coefficient greater than zero? Do two correlation coefficients differ? Worksheet Functions for Correlation CORREL and PEARSON RSQ COVARIANCE.P and COVARIANCE.S Data Analysis Tool: Correlation Tabled output Multiple correlation Partial correlation Semipartial correlation Data Analysis Tool: Covariance Using Excel to Test Hypotheses about Correlation Worksheet functions: FISHER, FISHERINV Correlation Analysis on the iPad Chapter 16 It’s About Time A Series and Its Components A Moving Experience Lining up the trend Data analysis tool: Moving Average How to Be a Smoothie, Exponentially One-Click Forecasting Working with Time Series on the iPad Chapter 17 Nonparametric Statistics Independent Samples Two samples: Mann-Whitney U test More than two samples: Kruskal-Wallis one-way ANOVA Matched Samples Two samples: Wilcoxon matched-pairs signed ranks More than two samples: Friedman two-way ANOVA More than two samples: Cochran’s Q Correlation: Spearman’s rS A Heads-Up Part 4 Probability Chapter 18 Introducing Probability What Is Probability? Experiments, trials, events, and sample spaces Sample spaces and probability Compound Events Union and intersection Intersection, again Conditional Probability Working with the probabilities The foundation of hypothesis testing Large Sample Spaces Permutations Combinations Worksheet Functions FACT PERMUT and PERMUTIONA COMBIN and COMBINA Random Variables: Discrete and Continuous Probability Distributions and Density Functions The Binomial Distribution Worksheet Functions BINOM.DIST and BINOM.DIST.RANGE NEGBINOM.DIST Hypothesis Testing with the Binomial Distribution BINOM.INV More on hypothesis testing The Hypergeometric Distribution HYPGEOM.DIST Chapter 19 More on Probability Discovering Beta BETA.DIST BETA.INV Poisson POISSON.DIST Working with Gamma The gamma function and GAMMA The gamma distribution and GAMMA.DIST GAMMA.INV Exponential EXPON.DIST Chapter 20 Using Probability: Modeling and Simulation Modeling a Distribution Plunging into the Poisson distribution Visualizing the Poisson distribution Working with the Poisson distribution Using POISSON.DIST again Testing the model’s fit A word about CHISQ.TEST Playing ball with a model A Simulating Discussion Taking a chance: The Monte Carlo method Loading the dice Data analysis tool: Random Number Generation Simulating the Central limit Theorem Simulating a business Chapter 21 Estimating Probability: Logistic Regression Working Your Way Through Logistic Regression Mining with XLMiner Part 5 The Part of Tens Chapter 22 Ten (12, Actually) Statistical and Graphical Tips and Traps Significant Doesn’t Always Mean Important Trying to Not Reject a Null Hypothesis Has a Number of Implications Regression Isn’t Always Linear Extrapolating Beyond a Sample Scatterplot Is a Bad Idea Examine the Variability Around a Regression Line A Sample Can Be Too Large Consumers: Know Your Axes Graphing a Categorical Variable as a Quantitative Variable Is Just Plain Wrong Whenever Appropriate, Include Variability in Your Graph Be Careful When Relating Statistics Textbook Concepts to Excel It’s Always a Good Idea to Use Named Ranges in Excel Statistical Analysis with Excel on the iPad Is Pretty Good! Chapter 23 Ten Topics (Thirteen, Actually) That Just Don’t Fit Elsewhere Graphing the Standard Error of the Mean Probabilities and Distributions PROB WEIBULL.DIST Drawing Samples Testing Independence: The True Use of CHISQ.TEST Logarithmica Esoterica What is a logarithm? What is e? LOGNORM.DIST LOGNORM.INV Array Function: LOGEST Array Function: GROWTH The logs of Gamma Sorting Data Part 6 Appendices Appendix A When Your Data Live Elsewhere Appendix B Tips for Teachers (and Learners) Augmenting Analyses Is a Good Thing Understanding ANOVA Revisiting regression Simulating Data Is Also a Good Thing When All You Have Is a Graph Appendix C More on Excel Graphics Tasting the Bubbly Taking Stock Scratching the Surface On the Radar Growing a Treemap and Bursting Some Sun Building a Histogram Ordering Columns: Pareto Of Boxes and Whiskers 3D Maps Filled Maps Appendix D The Analysis of Covariance Covariance: A Closer Look Why You Analyze Covariance How You Analyze Covariance ANCOVA in Excel Method 1: ANOVA Method 2: Regression After the ANCOVA And One More Thing Index EULA
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