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Feb 1, 2024 by George Taylor (gtaylor)
Apr 19, 2024 by Cory Williams (cwilliam)
Viewing outcome relationships between
MTHM 168 - STATISTICS
and
152 - Data Analytics - Tools and Techniques
Last approved:
Fri, 19 Apr 2024 16:33:14 GMT
Last edit:
Fri, 19 Apr 2024 16:33:12 GMT
Program Code
152 - Data Analytics - Tools and Techniques
Course Code
MTHM 168 - STATISTICS
Learning Outcomes Relationships
PLO 2: Utilize the industry common tools to mine large data sets for relationships and other insights.
CLO 5: Construct and interpret a confidence interval for a population parameter (such as proportion, mean, difference in proportions and difference in means) by using percentiles of a bootstrap distribution.
CLO 6: Use a randomization distribution for a population proportion, mean, difference of proportions, and difference of means to perform the corresponding hypothesis test for a given sample and null hypothesis.
CLO 7: Use the normal distribution to interpret z-scores and compute probabilities.
CLO 10: Use either a normal or t-distribution, as appropriate, to obtain a margin of error and construct the corresponding confidence interval. Interpret the results.
CLO 11: Perform a full hypothesis test for a population proportion and mean using either a normal or t-distribution, as appropriate. This process should include: formulating a null and alternative hypothesis from a given claim, choosing a test statistic, describing the rejection criteria, making a decision using a p-value or critical value, drawing an appropriate conclusion, and describing Type I and Type II errors.
PLO 3: Utilize visualization techniques to discover useful information within large data sets and communicate them to an appropriate audience.
CLO 3: Summarize bivariate data using graphical and numerical summaries including scatter plots, correlation coefficients and least squares regression lines.
Key: 46