Download Chapter 22: ANOVA – You should understand what an ANOVA test

Math 210
Review for Final Exam
Final Exam Schedule:



12:00 class: Fri, May 6 at 8:00, VZN B30
1:00 class: Wed, May 4 at 2:00, VWF 104
2:00 class: Thur, May 5 at 10:30, VZN B30
*** Don’t forget to bring a calculator and your formula sheet(s). No sharing allowed.
The Final exam is cumulative.
Chapter 1: Picturing Distribution with Graphs – You should be able to construct and
interpret histograms, bar graphs, stemplots, pie charts, and time plots. You should be
able to determine if a distribution is symmetric or skewed, or if it has any outliers. You
should also know the difference between categorical and quantitative variables.
Chapter 2: Describing Distributions with Numbers – Given a data set, you should be
able to determine its mean, median, standard deviation, quartiles, and five number
summary. You should know when a mean is appropriate to use and when a median is
appropriate, and how the shape of a distribution affects the mean and median. You
should know what the interquartile range is and be able to construct boxplots.
Chapter 3: The Normal Distribution – You should know how to find the standardized
score (z) of a number from a Normal distribution. You should be able to find the
probability above, below or between given z-score(s) (using Normcdf). You should also
be able to give the value (x) given the probability (using invNorm). You should know
what the 68-95-99.7 rule is and how it is used. You should know how  and  differ
from x and s.
Chapter 4: Scatterplots and Correlation – You should know the difference between
explanatory and response variables. You should be able to construct a scatterplot and
describe its direction, form, and strength. You should know what correlation measures.
Chapter 5: Regression – You should be able to plot a regression line, use a regression
equation to predict an outcome for a given input, and know what the y-intercept and slope
mean in the context of the problem. You should know what r2 means. You should know
how to calculate residuals and make a residual plot. You should know what the
following terms mean and how they affect correlation and regressions: lurking variables,
influential observations, and extrapolation. You should know the relationship between
correlation and causation.
Chapter 6: Two-Way Tables – You should be able to read a two-way table and
understand the difference between marginal and conditional distributions. You should be
able to calculate conditional probabilities.
Chapter 7: Sampling – You should know what conditions lead to bias results when
sampling a population. You should know what the following mean: probability
sampling, SRS, stratified random sample.
Chapter 8: Experiments – You should know what the following terms mean:
treatments, subjects, factors, control, double-blind, matched-pairs.
Chapter 9: Introducing Probability – You should be able to describe what the
probability of some event means. You should also know the difference between a
parameter and a statistic. You should know what the following terms are: sample space,
event, complement, disjoint, random variable, probability distribution.
Chapter 10: Sampling Distribution – You should know what the Central Limit
Theorem is and how it is used. You should know what a sampling distribution is and
how its shape is different from the distribution of single observations. You should be
able to find probabilities, using the normal distribution, associated with a sampling
distribution.
Chapter 11: General Probability Rules – You should know and be able to use the four
basic rules for probability given on p. 281. You should be able to use the multiplication
rule for independent events. You should be able to find conditional probabilities. You
should be able to fill in Venn Diagrams and Tree Diagrams for two events.
Chapter 12: Binomial Distributions – You should know what a binomial distribution is,
when it can be used, and be able to determine probabilities associated with a binomial
distribution using the formula or your calculator. You should be able to determine the
mean and the standard deviation of a binomial count.
Chapters 13 and 14 are covered in the following chapters.
Chapter 15: Inference in Practice – You should know certain things to be aware of
when conducting a test of significance. You should know the difference between
statistically significant and practical significance. You should know what Type I erros
are.
Chapter 16: Inference about a Population Mean – You should know how to perform
a test of significance and determine a confidence interval for the mean of a population or
a matched pairs comparison. You should be able to write hypotheses, find the test
statistic, p-value, and mark these on a sketch of the distribution. You should be able to
write a conclusion in the context of the problem. You should know the assumptions and
limitations of using t-procedures. You should know how to calculate the standard error
of the mean.
Chapter 17: Two Sample Problems – You should know how to perform a test of
significance and determine a confidence interval for the difference in the means of two
populations. You should be able to write a conclusion in the context of the problem. You
should know how this test differs from a matched pairs test.
Chapter 18: Inference about Population Proportion – You should know how to
perform a test of significance and determine a confidence interval for a single population
proportion. You should be able to write hypotheses, find the test statistic, p-value, and
mark these on a sketch of the distribution. You should be able to write a conclusion in
the context of the problem. You should also be able to determine the sample size needed
to construct a confidence interval with a certain margin of error for a single population
proportion both with an estimated sample proportion and a totally unknown sample
proportion.
Chapter 19: Comparing Two Proportions - You should know how to perform a test of
significance and determine a confidence interval for a difference between two population
proportions. You should be able to write a conclusion in the context of the problem.
Chapter 20: Chi-Square Test – You should be able to perform a chi-square test for
independence of fit and for goodness of fit. You should know what this sort of test is
testing for, and what the general shape of the Chi-Square distribution is and its mean.
You should be able to write hypotheses, find the test statistic, p-value, and mark these on
a sketch of the distribution. You should be able to write a conclusion in the context of
the problem. You should know how to find the degrees of freedom.
Chapter 21: Inference for Regression – With the help of Minitab output you should be
able to find confidence intervals and perform tests of significance for the slope of the
regression equation. You should know the difference between a confidence interval and
a prediction interval for the output of a regression equation. You should be able to write
hypotheses, find the test statistic, p-value, and mark these on a sketch of the distribution.
You should be able to write a conclusion in the context of the problem.
Chapter 22: ANOVA – You should understand what an ANOVA test is testing for. You
should be able to “perform” an ANOVA test. That is, you should be able to write the
hypotheses, read the test statistic and the p-value off of the Minitab output or your
calculator and write a conclusion. You should also generally understand how the test
statistic is determined. You should be able to make a rough sketch of the F distribution,
and mark on it the F-statistic and corresponding p-value.