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STAT 243Z - Elementary Statistics I |
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Associated Term:
Fall 2023
Learning Objectives: Upon successful completion of this course, the student will be able to: 1. Critically read, interpret, report, and communicate the results of a statistical study along with evaluating assumptions, potential for bias, scope, and limitations of statistical inference a. Classify study designs and variable types and identify methods of summary and analysis 2. Produce and interpret summaries of numerical and categorical data as well as appropriate graphical and/or tabular representations a. Identify patterns and striking deviations from patterns in data b. Identify associations between variables for bivariate data c. Apply technology to calculate statistical summaries and produce graphical representations 3. Use the distribution of sample statistics to quantify uncertainty and apply the basic concepts of probability into statistical arguments a. Interpret point and interval estimates 4. Identify, conduct, and interpret appropriate parametric hypothesis tests a. Identify the appropriate test based on variable type b. Identify situations where a one or two tailed test would be appropriate c. Conduct tests of one and two means d. Conduct tests of one and two proportions e. Explain the distinction between statistical and practical significance and the potential for error in hypothesis test conclusions f. Apply technology to perform hypothesis tests calculations 5.Assess relationships in quantitative bivariate data a. Address questions relating correlation as a linear association between variables b. Distinguish between correlation and causation within data c. Apply technology to explore bivariate data 6. Calculate and interpret probabilities a. Demonstrate an understanding of probability experiments, outcomes, and events b. Recognize disjoint and independent events c. Find and interpret empirical probabilities, including compound and conditional probabilities d. Find probabilities and values for a normal distribution e. Calculate probabilities using uniform, binomial, and Poisson distributions Required Materials: Technical Requirements: |

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