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1,001 statistics practice problems for dummies
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| 概要 | 1001 practice statistics problems with answers and solution explanations. |
| 目次 | pt. I. The questions 1. Basic vocabulary Picking out the population, sample, parameter, and statistic Distinguishing quantitative and categorical variables Getting a handle on bias, variables and the mean Understanding different statistics and data analysis terms Using statistical techniques Working with the standard deviation 2. Descriptive statistics Understanding the mean and the median Surveying standard deviation and variance Employing the Empirical Rule Measuring relative standing with percentiles Delving into data sets and descriptive statistics 3. Graphing Interpreting pie charts Considering three-dimensional pie charts Interpreting bar charts Introducing other graphs Interpreting histograms Describing the center of a distribution Interpreting box plots Interpreting time charts 4. Random variables and the binomial distribution Comparing discrete and continuous random variables Understanding the probability distribution of a random variable Determining the mean of a discrete random variable Working with the variance of a discrete random variable Putting together the mean, variance, and standard deviation of a random variable Introducing binomial random variables Figuring out the mean, variance, and standard deviation of a binomial random variable Finding binomial probabilities with a formula Finding binomial probabilities with the binomial table Using the normal approximation to the binomial 5. The normal distribution Working with z-Scores and values of X Writing probability notations Introducing the Z-Table Finding probabilities for a normal distribution Digging deeper into z-Scores and probabilities Figuring out percentiles for a normal distribution 6. The t-Distribution Understanding the t-Distribution and comparing it to the Z-Distribution Using the t-Table Using the t-Distribution to calculate confidence intervals 7. Sampling distribution and the central limit theorem The basics of sampling distributions checking out random variables and sample means Examining standard error Surveying notation and symbols Understanding what affects standard error Connecting sample means and sampling distributions Looking at the Central Limit Theorem Sample mean calculations Finding probabilities for sample means Adding proportions to the mix Figuring out the standard error of the sample proportion Using the Central Limit theorem for proportions Matching z-Scores to sample proportions Finding approximate probabilities 8. Finding room for a margin of error Defining and calculating margin of error Using the formula for margin of error when estimating a population mean Finding appropriate z*-Values for given confidence levels Connecting margin of error to sample size Linking margin of error and population proportion 9. Confidence intervals: basics for single population means and proportions Introducing confidence intervals Components of confidence intervals Interpreting confidence intervals Spotting misleading confidence intervals Calculating a confidence interval for a population mean Determining the needed sample size Population proportion Connecting a population proportion to a survey Calculating a confidence interval for a population proportion 10. Confidence intervals for two population means and proportions Working with confidence intervals and population proportions Working with confidence intervals and population means Making calculations when population standard deviations are known Working with unknown population standard deviations and small sample sizes 11. Claims, tests, and conclusions Knowing when to use a hypothesis test Setting up null and alternative hypotheses Finding the test statistic and the p-Value Making decision based on alpha levels and test statistics Making conclusions Understanding type I and type II errors 12. Hypothesis testing basics for a single population mean: z- and t-Tests What you need to run a z-Test Determining null and alternative hypotheses Introducing p-Values Calculating the z-Test statistic Finding p-Values by doing a test of one population mean Drawing conclusion about hypotheses Knowing when to use a t-Test Connecting hypotheses to t-Tests Calculating test statistics Working with critical values of t Linking p-Values and t-Tests Drawing conclusion from t-Tests Performing a t-Test for a single population mean 13. Hypothesis tests for one proportion, two proportions, or two population means Comparing two independent population means Using the paired t-Test Comparing two population proportions 14. Surveys Planning and designing surveys Selecting samples and conducting surveys 15. Correlation Scatter plots Correlations 16. Simple linear regression Introducing the regression line Knowing the conditions for regression Examining the equation for calculating the least-squares regression line Finding the slope and y-intercept of a regression line Seeing how variables can change in a regression line Finding a regression line Connecting to correlation and linear relationships Determining whether variables are candidates for a linear regression analysis Describing linear relationships Making predictions Figuring out expected values and differences 17. Two-way tables and independence Introducing variables and two-way tables Reading a two-way table Interpreting a two-way table by using percentages Interpreting a two-way table by using counts Connecting conditional probabilities to two-way tables Investigating independent variables Calculating marginal probability and more Adding joint probability into the mix Conditional and marginal probabilities Figuring out the number of cells in a two-way table Including conditional probability Research designs pt. II. The answers 18. Answers Appendix : Tables for reference.続きを見る |
| 本文を見る | Full text available from Maruzen eBook Library |
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| 登録日 | 2020.06.27 |
| 更新日 | 2020.06.28 |