Click on the Objective to go to related problems or click on
"On Line Help" for on line reading.
After each objective appropriate sections in the
textbook by Rosner are listed.
The student will be able to:
- Objective 1:
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- Classify data as categorical without order, categorical with order or
continuous.
See On Line Help
- Objective 2:
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- Compute and interpret the three common
measures of central tendency: the mean, median and mode.
Sections 2.2 and 2.3
- Objective 3:
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- Compute and interpret the three common
measures of variability: the range, variance and standard
deviation.
Sections 2.4 and 2.5
- Objective 4:
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- Construct a histogram and sketch and interpret histograms
from grouped data.
Section 2.7
- Objective 5:
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- Compute the probability of the occurrence of compound
independent events.
Section 3.1 - 3.5
- Objective 6:
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- Determine if events are independent, and compute the
probability of compound dependent events.
Section 3.6
- Objective 7:
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- Compute unconditional probabilities from an exhaustive set of
conditional probabilities.
Section 3.6
- Objective 8:
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- Use Bayes' law to compute P(B given A) when P(A given B) is
known.
Section 3.7
- Objective 9 :
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- Compute and interpret sensitivity, specificity, predictive
value positive and predictive value negative.
Section 3.7
- Objective 10:
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- Compute the mean and standard deviation of a probability
mass function.
Sections 4.4 and 4.5
- Objective 11:
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- Compute probabilities based on the binomial distribution.
Sections 4.7-4.9
- Objective 12:
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- Compute probabilities based on the Poisson distribution.
- Objective 13:
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Compute probabilities using the normal distribution.
Sections 5.2-5.5
- Objective 14:
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- Compute probabilities using the normal approximation to the
binomial and Poisson distributions.
Sections 5.7, 5.8
- Objective 15:
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- Compute the standard error of a sample mean.
Section 6.5
- Objective 16:
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- Put confidence bounds around a sample mean when the
population variance is known and when it is not.
Section 6.5
- Objective 17:
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- Put confidence bounds around a binomially distributed
proportion using normal theory methods.
Section 6.7
- Objective 18:
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- Construct one sided confidence limits for any of the above
parameter estimates.
Section 6.9
- Objective 19:
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- Conduct one sample tests of means with a known population
variance.
Section 7.3, 7.4
- Objective 20:
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- Conduct one sample tests of means when the population variance is not
known.
Section 7.5
- Objective 21:
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- Find the power of a statistical test.
Section 7.6
- Objective 22:
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- 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 7.7
- Objective 23:
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- Conduct one sample tests of proportions using the normal theory
method.
Section 7.10
- Objective 24 :
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- Conduct one sample test of Poisson distributed rates using the
Chi square test.
Section 7.11.
- Objective 25:
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- Construct an F test to determine if two variances are equal.
Section 8.6
- Objective 26:
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- Conduct two sample t tests when the population variances are
equal.
Section 8.4
- Objective 27:
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- Conduct two sample t tests when the population variances are
not equal.
Section 8.7
- Objective 28:
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- Compute the nonparametric tests equivalent to two sample t tests.
Section 12.4
- Objective 29:
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- Conduct paired t tests.
Section 8.2
- :
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Compute nonparametric tests equivalent to the paired t test.
Section 12.3
- Objective 31:
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- Compute sample size requirements for two sample t tests.
Section 8.10
- Objective 32:
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- Conduct two sample tests of proportions.
Section 10.2
- Objective 33:
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- Conduct chi square tests of independence.
Section 10.2
- Objective 34:
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- Compute Fisher's exact test.
Section 10.5
- Objective 35:
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- Compute risk ratios and odds ratios and put confidence bounds
around odds ratios.
Section 10.4
- Objective 36:
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- Determine if a binary variable is a confounder.
On line help.
- Objective 37:
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- Determine if a binary variable is an effect modifier.
On line help
- Objective 38:
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- Conduct McNemar chi square tests for matched samples:
Section 10.6
- Objective 39:
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Compute Perason Product Moment correlation coefficients.
Section 11.10
- Objective 40:
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- Comduct t tests to test the hypothesis that a correlation coefficient
equals zero and z tests to determine if a correlation coefficient
equals a nonzero constant.
Section 11.11
- Objective 41:
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- Conduct z tests to determine if two correlation coefficients
are equal.
Section 11.11
- Objective 42:
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- Conduct F tests and t tests on beta coefficients to determine if
the relationship between two continuous variables is significant.
Section 11.4
- Objective 43
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- Conduct and interpret global F tests, partial F tests and t test
on coefficients in multiple regression.
Section 11.7
- Objective 44
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- Compute and interprete F tests for oneway analysis of variance.
Section 9.2-3
- Objective 45
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- Conduct and interpret Newman-Keuls post hoc tests
On line help
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