Information about Final Exam
The Final Exam will have exactly 30
amount of calculations neede will be similar to prior tests.
The Final Exam is comprehensive. Thus, all topics covered in the
course may be used as the base for the Final Exam, with some
emphasis on more advanced topics.
You are allowed the use
your textbook, two pages
of notes (one-sheet, two-sided) and a calculator
. Notes can
be either typewritten or handwritten. Please minimize the noise from
turning pages during the test.
All topics covered by Midterms 1-3 may be on the test.
Also, there is an additional practice test.
The solutions WILL NOT BE POSTED.
In addition, the following topics covered after Midterm 3
may be on the test:
Be able to calculate the \(\chi^2\) statistic.
Be able to calculate the degrees of freedom for 2-way tables.
Understand the distinction.
Know how independence is related to calculating expected cell values.
Understand the distinction between significance test and
goodness of fit test.
Know the purpose of one-way ANOVA: testing equality of means for block (stratified)
Know the mechanics of calculating the F-statistic and the degrees of freedom.
Be able to look up P-values in the F-distribution table.
Be able to formulate the null and alternative hypothesis for one-way ANOVA.
Familiarity with the terms used in ANOVA
You are expected to know the notations for the quantities used in ANOVA,
as exemplified by the practice problems:
- Sum of squares between groups.
- Sum of squares of error, or sum of squares within groups.
- Sum of squares total.
- Mean sum of squares between groups.
- Mean sum of square within groups.
- Degrees of freedom between groups.
- Degrees of freedom within groups.
- Degrees of freedom total.
- Coefficient of determination
- The number of groups
- The number of elements in the \(i\)-th sample, \(i=1,2,\ldots,I\)
Also, you should know the definitions and fundamental relationships
between these quantities.
You should be fluent in hypothesis testing fundamentals: formulating the null and alternative
hypotheses for different situations, choosing a suitable statistic, look up of P-values
You should be absolutely clear which technique to choose for a situation presented
to you. For example, be able to distinguish the following terms:
- Should I use z-statistic or t-statistic?
- Should I use one-sample or two-sample test?
- Does the situation call for the use of proportions vs. sample means?
- Should I find a confidence interval or conduct a parametric test?
- Should I use a \(\chi^2\) test or one-way ANOVA?
- Boxplot vs. bargraph.
- Mean vs. sample mean.
- Variance vs. Sample variance.
- Should I use sampe pooling?
- Replacement vs. no replacement.
- Binomial distribution vs. normal distribution.
Some points about the ANOVA