Stat 201 Exam 2 Topics List Spring 2014 Chapter 8 Linear Regression Four conditions for valid regression o Quantitative variables o Straight enough condition o Outlier condition o Does the plot thicken condition What is special about the regression least squares line compared to any other line drawn through the data Given JMP output write out the regression model with actual variable names Interpret regression coefficients b0 and b1 Know when b0 has no logical interpretation Know the difference between y and y hat Be able to use a regression equation to make an estimate of y for a given value of x Be able to calculate and interpret a residual Be able to interpret a residuals plot and spot problems Be able to find r from r2 or vice versa o Taking care of the direction of the slope Interpretation of R square as the percentage of the variation in y associated with the variation in x Don t interpret the relationship to imply cause and effect Chapter 9 Regression Wisdom Understand extrapolation o Dangers o Valid only when one can safely assume that the model will hold outside the range of the data into the region where the extrapolation is desired Groups in residual plots Correlation is not causation Lurking variable and how they explain a correlation that is not due to causation Identify outliers from a scatter plot Decision Trees from class notes Response and explanatory variables o One y variable o Multiple x variables Partitioning the data o R2 increases with each partition o When to stop partitioning Illogical partitions Small increases in R2 Interpreting the tree o Interpretation of R2 o Leaf report 1 Chapter 11 Understanding Randomness Understand what random means Simulations and associated terminology Chapter 12 Sample surveys Populations and samples Parameters and statistics Representative samples Sampling frame Nonrandom Bad samples o Voluntary samples o Convenience samples Randomized samples o Simple random samples o Stratified random samples o Cluster random samples o Systematic samples o Multistage samples Sampling biases o Nonresponse o Undercoverage o Response bias Chapter 14 What is Probability Probabilities have to be between 0 and 1 inclusive What it means to have a probability of 0 or 1 Recognize valid and invalid assignments of probabilities Law of large numbers Know that disjoint is the same as mutually exclusive and means that two events that can t happen at the same time Know what it means for two events to be independent Know that disjoint events are never independent and independent events are never disjoint Understand the addition rule and necessary conditions for using this rule Be able to apply this rule Understand the multiplication rule and necessary conditions for using this rule Be able to apply this rule Understand complement rule and be able to apply it P A 1 P A o Recognize that when the words probability of at least are used this many times involves using this rule State whether or not it would be reasonable to assume a set of events is independent or disjoint 2 Chapter 18 Sampling Distribution Models some info on probability Discrete random variables Probability distribution Probability mass function pmf What it means for trials to be independent Know the difference between a population and a sample Know what p and p represent Have a general understanding of what a sampling distribution is Know how to find the mean and standard deviation of the sampling distribution of p given the known population proportion p and the sample size n Know when the shape of a sampling distribution of p is approximately Normal o Success failure condition o Independence condition or as a practical approximation the randomization and 10 conditions Be able to use the 68 95 99 7 rule to find the approximate probability of a specific p or greater or less from a normally distributed sampling distribution of p Know the difference between a population and a sample Know what y and represent Have a general understanding of what a sampling distribution is Have a general understanding of the Central Limit Theorem Know assumptions for CLT o Independence condition or as a practical approximation the randomization and 10 conditions o Large enough sample condition Know the difference between two distributions o Real world distribution of the sample that one might see in a histogram o Math world distribution of a sample statistic such as the sample mean Given the mean and standard deviation of a population be able to calculate the mean and standard deviation of the sampling distribution of y given the sample size n 3 Chapter 19 Confidence Intervals for Proportions Standard error for proportions o How it is related to the standard deviation for proportions Being able to calculate a confidence interval with the aid of the formula sheet Meaning of confidence Margin of error Trade off between certainty and precision in confidence intervals Critical values o Being able to read the output of this applet http davidmlane com hyperstat z table html Assumptions o Independence Randomization 10 condition o Success Failure condition Interpreting JMP output 4
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