Learning Support for Statistical Reasoning - MDE 55 at Eastern Shore Community College

https://courses.vccs.edu/colleges/escc/courses/MDE55-LearningSupportforStatisticalReasoning

Effective: 2020-01-01

Course Description

Provides support to ensure success for students co-enrolled in Statistical Reasoning (MTH 155). Course will review foundational topics through direct instruction, guided practice, and individualized support.
Lecture 3 credits. Total 3 hours per week.
3 credits

The course outline below was developed as part of a statewide standardization process.

General Course Purpose

This course provides support to ensure student success with the MTH 155 objectives.

Course Prerequisites/Corequisites

Corequisite: MTH 155

Course Objectives

• Communication
• Interpret and communicate quantitative information and mathematical and statistical concepts using language appropriate to the context and intended audience
• Use appropriate statistical language in oral, written, and graphical terms.
• Read and interpret graphs and descriptive statistics.
• Problem Solving
• Make sense of problems, develop strategies to find solutions, and persevere in solving them.
• Understand what statistical question is being addressed, use appropriate strategies to answer the question of interest, and state conclusions using appropriate statistical language.
• Reasoning
• Reason, model, and draw conclusions or make decisions with quantitative information.
• Use probability, graphical, and numerical summaries of data, confidence intervals, and hypothesis testing methods to make decisions.
• Use probability, graphical, and numerical summaries of data, confidence intervals, and hypothesis testing methods to make decisions.
• Evaluation
• Critique and evaluate quantitative arguments that utilize mathematical, statistical, and quantitative information.
• Identify errors such as inappropriate sampling methods, sources of bias, and potentially confounding variables, in both observational and experimental studies.
• Identify mathematical or statistical errors, inconsistencies, or missing information in arguments.
• Technology
• Use appropriate technology in a given context.
• Use some form of spreadsheet application to organize information and make repeated calculations using simple formulas and statistical functions.
• Use technology to calculate descriptive statistics and test hypotheses.
• Graphical and Numerical Data Analysis
• Identify the difference between quantitative and qualitative data
• Identify the difference between discrete and continuous quantitative data
• Construct and interpret graphical displays of data, including (but not limited to) box plots, line charts, histograms, and bar charts
• Construct and interpret frequency tables
• Compute measures of center (mean, median, mode), measures of variation, (range, interquartile range, standard deviation), and measures of position (percentiles, quartiles, standard scores)
• Sampling and Experimental Design
• Recognize a representative sample and describe its importance
• Identify methods of sampling
• Explain the differences between observational studies and experiments
• Recognize and explain the key concepts in experiments, including the selection of treatment and control groups, the placebo effect, and blinding
• Probability Concepts
• Describe the difference between relative frequency and theoretical probabilities and use each method to calculate probabilities of events
• Calculate probabilities of composite events using the complement rule, the addition rule, and the multiplication rule.
• Use the normal distribution to calculate probabilities
• Identify when the use of the normal distribution is appropriate.
• Recognize or restate the Central Limit Theorem and use it as appropriate.
• Statistical Inference
• Explain the difference between point and interval estimates.
• Construct and interpret confidence intervals for population means and proportions.
• Interpret the confidence level associated with an interval estimate.
• Conduct hypothesis tests for population means and proportions.
• Interpret the meaning of both rejecting and failing to reject the null hypothesis.
• Use a p-value to reach a conclusion in a hypothesis test.
• Identify the difference between practical significance and statistical significance.
• Correlation and Regression
• Analyze scatterplots for patterns, linearity, and influential points
• Determine the equation of a least-squares regression line and interpret its slope and intercept.
• Calculate and interpret the correlation coefficient and the coefficient of determination.
• Categorical Data Analysis
• Conduct a chi-squared test for independence between rows and columns of a two-way contingency table.

Major Topics to be Included

• Arithmetic and order of operations
• Operations with fractions, percentages, and decimals
• Exponents
• Formulas
• Units and measurement
• Simplifying algebraic expressions and solving linear equations
• Using technology including calculators and spreadsheet software

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