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Introduction to Descriptive Statistics
- Recognize and define key terms: element, variable, observation, data set, quantitative, qualitative, discrete, continuous variables.
- Apply probability and non-probability sampling methods.
- Create and interpret frequency tables, interpret graphs, histograms and box plots.
- Differentiate between quantitative and qualitative data and levels of measurement.
- Understand quartiles, percentiles, central tendency and variability.
Basic Probability and Random Variables
- Determine events (mutually exclusive and independent), Venn diagram, contingency table, and tree diagrams.
- Differentiate between discrete, continuous, and conditional probability.
- Describe a random variable and its characteristics.
- Create and interpret probability distributions.
Normal Distribution and Central Limit Theorem
- Describe the purpose and characteristics of the normal curve.
- Use the normal curve to find probabilities.
- Summarize sampling error.
- Create and interpret confidence intervals for the mean.
- Define the role of central limit theorem.
- Differentiate between type I and type II errors.
- Describe hypothesis testing.
- Calculate and interpret hypothesis tests for the difference between two means.
- Interpret data analysis results to reach conclusions.
- Create and interpret chi-square tests.
- Calculate and interpret linear regression: line of best fit, correlation coefficient, and outliers.
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