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Apr 2, 2024 by Cory Williams (cwilliam)
Viewing outcome relationships between
MTHM 168 - STATISTICS
and
124 - Manufacturing Engineering Technology – Quality Assurance
Last approved:
Tue, 02 Apr 2024 14:23:43 GMT
Last edit:
Tue, 02 Apr 2024 14:23:40 GMT
Program Code
124 - Manufacturing Engineering Technology – Quality Assurance
Course Code
MTHM 168 - STATISTICS
Learning Outcomes Relationships
PLO 1: Apply basic quality problem solving tools and techniques to manufacturing process centered problems for quality improvement.
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 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.
PLO 5: Effectively employ lean principles and six sigma process applications in oral presentations and written legal documents.
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.
Key: 589