Click on the Objective to go to related problems. After each objective appropriate sections in the textbook by Daniel are listed.

The student will be able to:

Objective 1

Determine if a variable is binary, categorical without order, categorical with order or continuous.

Section 1.3

Objective 2:

Compute and interpret the three common measures of central tendency: the mean, median and mode.

Sections 2.4 and 2.6

Objective 3:

Compute and interpret the three common measures of variability: the range, variance and standard deviation.

Sections 2.5 and 2.7

Objective 4:

Compute the probability of the occurrence of compound independent events.

Section 3.4

Objective 5:

Determine if events are independent and compute the probability of compound dependent events.

Section 3.4

Objective 6:

Compute and interpret relative risk.

On line help

Objective 7:

Compute unconditional probabilities from an exhaustive set of conditional probabilities.

On line help

Objective 8:

Use Bayes' law to compute P(B given A) when P(A given B) is known.

On line help

Objective 9:

Compute and interpret sensitivity, specificity, predictive value positive and predictive value negative.

On line help

Objective 10:

Compute probabilities of evnents given a discrete probability distribution.

Sections 4.2

Objective 11:

Compute probabilities based on the binomial distribution.

Sections 4.3

Objective 12:

Compute probabilities based on the Poisson distribution.

Section 4.4

Objective 13:

Compute probabilities using the normal distribution.

Sections 4.6-4.7

Objective 14:

Compute the standard error of a sample mean.

Section 5.3

Objective 15:

Put confidence bounds around a sample mean when the population variance is known and when it is not know.

Section 6.2, 6.3

Objective 16:

Put confidence bounds around a binomially distributed proportion using normal theory methods.

Section 6.5

Objective 17:

Put a confidence bound around an odds ratio.

On line help

Objective 18:

Find the required sample size for the one sample test of a mean given the expected difference, probability of type one error and power.

Section 6.7

Objective 19:

Conduct one sample tests of means with a known population variance.

Section 7.2

Objective 20:

Conduct one sample tests of means when the population variance is not known.

Section 7.2

Objective 21:

Conduct one sample tests of proportions using the normal theory method.

Section 7.5

Objective 22:

Construct an F test to determine if two variances are equal.

Section 7.8

Objective 23:

Conduct two sample t tests when the population variances are equal.

Section 7.3

Objective 24:

Conduct two sample t tests when the population variances are not equal.

Section 7.3

Objective 25:

Conduct paired t tests.

Section 7.4

Objective 26:

Compute sample size requirements for two sample t tests.

Section 7.9 - 7.10

Objective 27:

Conduct two sample tests of proportions.

Section 7.6

Objective 28:

Conduct chi square tests of independence.

Section 12.4

Objective 29:

Conduct Fisher Exact tests for small samples.

Section 12.6

Objective 30:

Conduct McNemar chi sqduare tests for matched samples:

On line help

Objective 31:

Comduct t tests of the hypothesis that a correlation coefficent equals zero and z tests to determine if correlations coefficients equal a constant. Section 9.7

Objective 32:

Conduct F tests and t tests on beta coefficients to determine if the relationship between two continuous variables is significant.

Section 9.2 - 9.5

Objective 33

Conduct nonparametric tests equivalent to one sample t tests.

Section 13.3

Objective 34

Compute nonparametric tests equivalent to two sample t tests

. Section 13.6

Objective 35

Compute nonparametric equivalents to the Pearson product moment correlation coefficient.

Section 13.10

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