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Statistics Essentials for Dummies

ISBN-10: 0470618396
ISBN-13: 9780470618394
Edition: 2010
Authors: Deborah Rumsey
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Description: A new series extension of the For Dummies brand, The Essentials For Dummies will appeal to the huge number of readers who seek out focused, short form consumer reference books at the $9.99 price point. Positioned for students (and parents) who just  More...

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Book details

List price: $13.95
Copyright year: 2010
Publisher: John Wiley & Sons, Incorporated
Publication date: 4/30/2010
Binding: Paperback
Pages: 192
Size: 5.60" wide x 8.60" long x 0.44" tall
Weight: 0.660
Language: English

A new series extension of the For Dummies brand, The Essentials For Dummies will appeal to the huge number of readers who seek out focused, short form consumer reference books at the $9.99 price point. Positioned for students (and parents) who just want the key concepts and a few examples without the review, ramp-up, and anecdotal content The Essentials For Dummies series is a perfect solution for exam-cramming, homework help, and reference.

Introduction
About This Book
Conventions Used in This Book
Foolish Assumptions
Icons Used in This Book
Where to Go from Here
Statistics in a Nutshell
Designing Studies
Surveys
Experiments
Collecting Data
Selecting a good sample
Avoiding bias in your data
Describing Data
Descriptive statistics
Charts and graphs
Analyzing Data
Making Conclusions
Descriptive Statistics
Types of Data
Counts and Percents
Measures of Center
Measures of Variability
Percentiles
Finding a percentile
Interpreting percentiles
The Five-Number Summary
Charts and Graphs
Pie Charts
Bar Graphs
Time Charts
Histograms
Making a histogram
Interpreting a histogram
The distribution of the data in a histogram
Variability in the data from a histogram
Center of the data from a histogram
Evaluating a histogram
Boxplots
Making a boxplot
Interpreting a boxplot
Distribution of data in a boxplot
Variability in a data set from a boxplot
Center of the data from a boxplot
The Binomial Distribution
Characteristics of a Binomial
Checking the binomial conditions step by step
Non-binomial examples
No fixed number of trials
More than success or failure
Probability of success (p) changes
Trials are not independent
Finding Binomial Probabilities Using the Formula
Finding Probabilities Using the Binomial Table
Finding probabilities when p ≤ 0.50
Finding probabilities when p > 0.50
Finding probabilities for X greater-than, less-than, or between two values
The Expected Value and Variance of the Binomial
The Normal Distribution
Basics of the Normal Distribution
The Standard Normal (Z) Distribution
Finding Probabilities for X
Finding X for a Given Probability
Normal Approximation to the Binomial
Sampling Distributions and the Central Limit Theorem
Sampling Distributions
The mean of sampling distribution
The standard error of a sampling distribution
Sample size and standard error
Population standard deviation and standard error
The shape
Distribution of X is normal
Distribution of X is unknown or not normal
Finding Probabilities for X
The Sampling Distribution of the Sample Proportion
What proportion of students need math help?
Finding Probabilities for p
Confidence Intervals
Making Your Best Guesstimate
The Goal: Small Margin of Error
Choosing a Confidence Level
Factoring In the Sample Size
Counting On Population Variability
Confidence Interval for a Population Mean
Confidence Interval for a Population Proportion
Confidence Interval for the Difference of Two Means
Confidence Interval for the Difference of Two Proportions
Interpreting Confidence Intervals
Spotting Misleading Confidence Intervals
Hypothesis Tests
Doing a Hypothesis Test
Identifying what you're testing
Setting up the hypotheses
What's the alternative?
Knowing which hypothesis is which
Finding sample statistics
Standardizing the evidence: the test statistic
Weighing the evidence and making decisions: p-values
Finding the p-value
Interpreting a p-value
General steps for a hypothesis test
Testing One Population Mean
Testing One Population Proportion
Comparing Two Population Means
Testing the Mean Difference: Paired Data
Testing Two Population Proportions
You Could Be Wrong: Errors in Hypothesis Testing
A false alarm: Type-1 error
A missed detection: Type-2 error
The t-distribution
Basics of the t-Distribution
Understanding the t-Table
t-distributions and Hypothesis Tests
Finding critical values
Finding p-values
t-distributions and Confidence Intervals
Correlation and Regression
Picturing the Relationship with a Scatterplot
Making a scatterplot
Interpreting a scatterplot
Measuring Relationships Using the Correlation
Calculating the correlation
Interpreting the correlation
Properties of the correlation
Finding the Regression Line
Which is X and which is Y?
Checking the conditions
Understanding the equation
Finding the slope
Finding the y-intercept
Interpreting the slope and y-intercept
Interpreting the slope
Interpreting the y-intercept
The best-fitting line for the crickets
Making Predictions
Avoid Extrapolation!
Correlation Doesn't Necessarily Mean Cause-and-Effect
Two-Way Tables
Organizing and Interpreting a Two-way Table
Defining the outcomes
Setting up the rows and columns
Inserting the numbers
Finding the row, column, and grand totals
Finding Probabilities within a Two-Way Table
Figuring joint probabilities
Calculating marginal probabilities
Finding conditional probabilities
Checking for Independence
A Checklist for Samples and Surveys
The Target Population is Well Defined
The Sample Matches the Target Population
The Sample Is Randomly Selected
The Sample Size Is Large Enough
Nonresponse Is Minimized
The importance of following up
Anonymity versus confidentiality
The Survey Is of the Right Type
Questions Are Well Worded
The Timing Is Appropriate
Personnel Are Well Trained
Proper Conclusions Are Made
A Checklist for Judging Experiments
Experiments versus Observational Studies
Criteria for a Good Experiment
Inspect the Sample Size
Small samples - small conclusions
Original versus final sample size
Examine the Subjects
Check for Random Assignments
Gauge the Placebo Effect
Identify Confounding Variables
Assess Data Quality
Check Out the Analysis
Scrutinize the Conclusions
Overstated results
Ad-hoc explanations
Generalizing beyond the scope
Ten Common Statistical Mistakes
Misleading Graphs
Pie charts
Bar graphs
Time charts
Histograms
Biased Data
No Margin of Error
Nonrandom Samples
Missing Sample Sizes
Misinterpreted Correlations
Confounding Variables
Botched Numbers
Selectively Reporting Results
The Almighty Anecdote
Appendix: Tables for Reference
Index

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