Viewing outcome relationships between MTHM 168 - STATISTICS and 24 - Associate Degree Nursing

Last approved: Mon, 13 May 2024 13:01:28 GMT

Last edit: Wed, 08 May 2024 20:17:56 GMT

Changes proposed by: Mary Grady (mgrady)
24 - Associate Degree Nursing
MTHM 168 - STATISTICS
  • PLO 2: Integrate best current evidence with clinical expertise and patient/family preferences and values for delivery of optimal health care. (EBP)
    • CLO 1: Describe and interpret univariate data using graphical summaries such as box-plots, histograms, pie charts, bar charts and dot plots.
    • CLO 2: Describe and interpret univariate data using numerical summaries such as proportions, mean, median, percentiles and standard deviation.
    • CLO 3: Summarize bivariate data using graphical and numerical summaries including scatter plots, correlation coefficients and least squares regression lines.
    • CLO 4: Apply basic concepts of probability such as sample spaces, events (independent or dependent) and their associated probabilities using addition and multiplication rules.
    • 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 8: Describe the principles of data collection including randomization, sampling design, and comparison. Distinguish between observational and experimental studies.
    • CLO 9: Apply the Central Limit Theorem to obtain the approximate sampling distributions of means and proportions.
    • 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: Prioritize data to monitor the outcomes of care processes in order to ensure patient safety and minimize risk of harm. (quality improvement/safety)
    • CLO 1: Describe and interpret univariate data using graphical summaries such as box-plots, histograms, pie charts, bar charts and dot plots.
    • CLO 3: Summarize bivariate data using graphical and numerical summaries including scatter plots, correlation coefficients and least squares regression lines.
    • CLO 4: Apply basic concepts of probability such as sample spaces, events (independent or dependent) and their associated probabilities using addition and multiplication rules.
    • 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 8: Describe the principles of data collection including randomization, sampling design, and comparison. Distinguish between observational and experimental studies.
    • 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.
Key: 1492