- Catalog Home
- » Statistics for dummies
Statistics for dummies
Author
Publisher
Varies, see individual formats and editions
Publication Date
Varies, see individual formats and editions
Language
English
Description
Loading Description...
Table of Contents
From the Book - Second edition.
Vital statistics about statistics
Number-crunching basics
Distributions and the central limit theorem
Guesstimating and hypothesizing with confidence
Statistical studies and the hunt for a meaningful relationship
The part of tens
Appendix: Tables for reference.
From the Book - Second edition.
Pt. 1. Vital statistics about statistics : Statistics in a nutshell ; The statistics of everyday life ; Taking control : so many numbers, so little time ; Tools of the trade
Pt. 2. Number-crunching basics : Means, medians, and more ; Getting the picture : graphing categorical data ; Going by the numbers : graphing numerical data
Pt. 3. Distributions and the central limit theorem : Random variables and the binomial distribution ; The normal distribution ; The t-distribution ; Sampling distributions and the central limit theorem
Pt. 4. Guesstimating and hypothesizing with confidence : Leaving room for a margin of error ; Confidence intervals : making your best guesstimate ; Claims, tests, and conclusions ; Commonly used hypothesis tests : formulas and examples
Pt. 5. Statistical studies and the hunt for a meaningful relationship : Polls, polls, and more polls ; Experiments : medical breakthroughs or misleading results? ; Looking for links : correlation and regression ; Two-way tables and independence
Pt. 6. The part of tens : Ten tips for the statistically savvy sleuth ; Ten surefire exam score boosters.
From the Book
Introduction: -- About this book -- Foolish assumptions -- Beyond the book -- Where to go from here -- Part 1: Getting Started With Statistics: -- Statistics Of Everyday Life: -- Statistics and the media: more questions than answers?: -- Probing popcorn problems -- Venturing into viruses -- Comprehending crashes -- Mulling malpractice -- Belaboring the loss of land -- Scrutinizing schools -- Study sports -- Banking on business news -- Touring the travel news -- Surveying sexual stats -- Breaking down weather reports -- Using statistics at work: -- Delivering babies-and information -- Posing for pictures -- Poking through pizza data -- Statistics in the office -- Taking Control: So Many Numbers, So Little Time: -- Detecting errors, exaggerations, and just plain lies: -- Checking the math -- Uncovering misleading statistics -- Looking for lies in all the right places -- Feeling the impact of misleading statistics -- Tools Of The Trade: -- Thriving in a statistical world -- Statistics: more than just numbers -- Designing appropriate studies: -- Surveys (polls) -- Experiments -- Collecting quality data: -- Sample, random, or otherwise -- Bias -- Grabbing some basic statistical jargon: -- Data -- Data set -- Variable -- Population -- Statistic -- Parameter -- Mean (average) -- Median -- Standard deviation -- Percentile -- Standard score -- Distribution and normal distribution -- Central limit theorem -- z-values -- Margin of error -- Confidence interval -- Hypothesis testing -- p-values -- Statistical significance -- Correlation, regression, and two-way tables -- Drawing credible conclusions: -- Reeling in overstated results -- Questioning claims of cause and effect -- Becoming a sleuth, not a skeptic -- Part 2: Number-Crunching Basics: -- Crunching Categorical Data: -- Summing up data with descriptive statistics -- Crunching categorical data: tables and percent's: -- Counting on the frequency -- Relating with percentages -- Two-way tables: summarizing multiple measures -- Interpreting counts and percent's with caution -- Means, Medians, And More: -- Measuring the center with mean and median: -- Averaging out to the mean -- Splitting your data down the median -- Comparing means and medians: histograms -- Accounting for variation: -- Reporting the standard deviation -- Being out of range -- Examining the empirical rule (68-95-99-7) -- Measuring relative standing with percentiles: -- Calculating percentiles -- Interpreting percentiles -- Gathering a five-number summary -- Exploring interquartile range -- Getting The Picture: Graphing Categorical Data: -- Take another little piece of my pie chart: -- Tallying personal expenses -- Bringing in a lotto revenue -- Ordering takeout -- Projecting age trends -- Raising the bar on bar graphs: -- Tracking transportation expenses -- Making a lotto profit -- Tipping the scales on a bar graph -- Pondering pet peeves -- Going By The Numbers: Graphing Numerical Data: -- Handling histograms: -- Making a histogram -- Interpreting a histogram -- Putting numbers with pictures -- Detecting misleading histograms -- Examining boxplots: -- Making a boxplot -- Interpreting a boxplot -- Tackling time charts: -- Interpreting time charts -- Understanding variability: time charts versus histograms -- Spotting misleading time charts -- Part 3: Distributions And The Central Limit Theorem: -- Coming To Terms With Probability: -- Set notation overview: -- Noting outcomes: sample spaces -- Noting subsets of sample spaces: events -- Noting a void in the set: empty sets -- Putting sets together: unions, intersections, and complements -- Probabilities of events involving A and/or B: -- Probability notation -- Marginal probabilities -- Union probabilities -- Intersection (joint) probabilities -- Complement probabilities -- Conditional probabilities -- Understanding and applying the rules of probability: -- Complement rule (for opposites, not for flattering a date) -- Multiplication rule (for intersections, not for rabbits) -- Addition rule (for unions of the nonmarital nature) -- Recognizing independence in multiple events: -- Checking independence for two events with the definition -- Using the multiplication rule for independent events -- Including mutually exclusive events: -- Recognizing mutually exclusive events: -- Simplifying the addition rule with mutually exclusive events -- Distinguishing independent from mutually exclusive events: -- Comparing and contrasting independence and exclusivity -- Checking for independence or exclusivity in a 52-card deck -- Avoiding probability misconceptions -- Predictions using probability -- Random Variables And The Binomial Distribution: -- Defining a random variable: -- Discrete versus continuous -- Probability distributions -- Mean and variance of a discrete random variable -- Identifying a binomial: -- Checking binomial conditions step by step -- No fixed number of trials -- More than success or failure -- Trials are not independent -- Probability of success (p) changes -- Finding binomial probabilities using a formula -- Finding probabilities using the binomial table: -- Finding probabilities for specific values of x -- Finding probabilities for x greater-than, less-than, or between two values -- Checking out the mean and standard deviation of the binomial -- Normal Distribution: -- Exploring the basics of the normal distribution -- Meeting the standard normal (Z-) distribution: -- Checking out Z -- Standardizing from X to Z -- Finding probabilities for Z with the Z-table -- Finding probabilities for a normal distribution -- Knowing where you stand with percentiles -- Finding X when you know the percent: -- Figuring out a percentile for a normal distribution -- Translating tricky wording in percentile problems -- Normal approximation to the binomial -- t-Distribution: -- Basics of the t-distribution: -- Comparing the t- and Z-distributions -- Discovering the effect of variability on t-distributions -- Using the t-table: -- Finding probabilities with the t-table -- Figuring percentiles for the t-distribution -- Picking out t*-values for confidence intervals -- Studying behavior using the t-table -- Sampling Distributions And the Central Limit Theorem: -- Defining a sampling distribution -- Mean of a sampling distribution -- Measuring standard error: -- Sample size and standard error -- Population standard deviation and standard error -- Looking at the shape of a sampling distribution: -- Case 1: Distribution of X is normal -- Case 2: Distribution of X is not normal-enter the central limit theorem -- Finding probabilities for the sample mean -- Sampling distribution of the sample proportion -- Finding probabilities for the sample proportion --
Part 4: Guesstimating And Hypothesizing With Confidence:
Leaving Room For A Margin Of Error:
Seeing the importance of that plus or minus
Finding the margin of error: a general formula:
Measuring sample variability
Calculating margin of error for a sample proportion
Reporting results
Calculating margin of error for a sample mean
Being confident you're right
Determining the impact of sample size:
Sample size and margin of error
Bigger isn't always (that much) better!
Keeping margin of error in perspective
Confidence Intervals: Making Your Best Guesstimate:
Not all estimates are created equal
Linking a statistic to a parameter
Getting with the jargon
Interpreting results with confidence
Zooming in on width
Choosing a confidence level
Factoring in the sample size
Counting on population variability
Calculating a confidence interval for a population mean:
Case 1: Population standard deviation is known
Case 2: Population standard deviation is unknown and/or n is small
Figuring out what sample size you need
Determining the confidence interval for one population proportion
Creating a confidence interval for the difference of two means:
Case 1: Population standard deviations are known
Case 2: Population standard deviations are unknown and/or sample sizes are small
Estimating the difference of two proportions
Spotting misleading confidence intervals
Claims, Tests, And Conclusions:
Setting up the hypotheses:
Defining the null
What's the alternative?
Gathering good evidence (data)
Compiling the evidence: the test statistic:
Gathering sample statistics
Measuring variability using standard errors
Understanding standard scores
Calculating and interpreting the test statistic
Weighing the evidence and making decisions: p-values:
Connecting test statistics and p-values
Defining a p-value
Calculating a p-value
Making conclusions:
Setting boundaries for rejecting H
Testing varicose veins
Assessing the chance of a wrong decision:
Making a false alarm: type I errors
Missing out on a detection: type II errors
Commonly Used Hypothesis Tests: Formulas And Examples:
Testing one population mean
Handling small samples and unknown standard deviations: the t-test:
Putting the t-test to work
Relating t to Z
Handling negative t-values
Examining the not-equal-to alternative
Drawing conclusions using the critical value
Testing one population proportion
Comparing two (independent) population averages
Testing for an average difference (the paired t-test)
Comparing two population proportions
Part 5: Statistical Studies And The Hunt For A Meaningful Relationship:
Polls, Polls, And More Polls:
Recognizing the impact of polls:
Getting to the source
Surveying what's hot
Impacting lives
Behind the scenes: the ins and outs of surveys:
Planning and designing a survey
Selecting the sample
Carrying out a survey
Interpreting results and finding problems
Experiments: Medical Breakthroughs Or Misleading Results?:
Boiling down the basics of studies:
Looking at the lingo of studies
Observing observational studies
Examining experiments
Designing a good experiment:
Designing the experiment to make comparisons
Selecting the sample size
Choosing the subjects
Making random assignments
Controlling for confounding variables
Respecting ethical issues
Collecting good data
Analyzing the data properly
Interpreting experiment results:
Making appropriate conclusions
Making informed decisions
Looking For Links: Correlation And Regression:
Picturing a relationship with a scatterplot:
Making a scatterplot
Interpreting a scatterplot
Quantifying linear relationships using the correlation:
Calculating the correlation
Interpreting the correlation
Examining properties of the correlation
Working with linear regression:
Figuring out which variable is X and which is Y
Checking the conditions
Calculating the regression line
Interpreting the regression line
Putting it all together with an example: the regression line for the crickets
Making proper predictions:
Checking the conditions
Staying in-bounds
Explaining the relationship: correlation versus cause and effort
Two-Way Tables And Independence:
Organizing a two-way table:
Setting up the cells
Figuring the totals
Interpreting two-way tables:
Singling out variables with marginal distributions
Examining all groups-a joint distribution
Comparing groups with conditional distributions
Checking independence and describing dependence:
Checking for independence
Describing a dependent relationship
Cautiously interpreting results:
Checking for legitimate cause and effect
Projecting from sample to population
Making prudent predictions
Resisting the urge to jump to conclusions
Part 6: Part Of Tens:
Ten Tips For The Statistically Savvy Sleuth:
Pinpoint misleading graphs:
Pie charts
Bar graphs
Time charts
Histograms
Uncover biased data
Search for a margin of error
Identify nonrandom samples
Sniff out missing sample sizes
Detect misinterpreted correlations
Reveal confounding variables
Inspect the numbers
Report selective reporting
Expose the anecdote
Ten Surefire Exam Score Boosters:
Know what you don't know, and then do something about it
Avoid "yeah-yeah" traps:
Yeah-Yeah Trap #1
Yeah-Yeah Trap #2
Make friends with formulas
Make an "if-then-how" chart
Figure out what the question is asking
Label what you're given
Draw a picture
Make the connection and solve the problem
Do the math-twice
Analyze your answers
Appendix:
Z-table
T-table
Binomial table
Index
Excerpt
Loading Excerpt...
Author Notes
Loading Author Notes...
More Details
Contributors
Unger, David,1950- author
ISBN
9780470911082
9780764554230
9781119084853
9781119293521
9780764554230
9781119084853
9781119293521
Reviews from GoodReads
Loading GoodReads Reviews.
Staff View
Loading Staff View.