mth218 | undergraduate

Statistics II

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Students apply elementary probability theory, descriptive and inferential statistics, and reasoning to real-world situations. The course embeds foundational skill into topics including probability, statistics, and reasoning.

This undergraduate-level course is 5 To enroll, speak with an Enrollment Representative.

Course details:

Credits: 3
Continuing education units: XX
Professional development units: XX
Duration: 5

topic title goes here

    Sampling Distributions and Central Limit Theorem

    • Explain how sampling error affects the need for sampling distributions.
    • Calculate the mean and standard deviation of a variable given mean and standard deviation of a population.
    • Apply the central limit theorem.
    • Determine the sampling distribution of the sample mean.
    • Explain the purpose of sampling distributions.

    Confidence Intervals and Estimates

    • Identify biased and unbiased estimators.
    • Review of sample versus populations and parameters versus statistics.
    • Calculate and interpret confidence intervals for proportions and means.
    • Calculate the required sample size to estimate a population proportion and mean.
    • Solve real world applications.

    Correlation and Regression

    • Interpret the slope and intercepts of a line.
    • Interpret the correlation of data from a graph.
    • Use technology to graph data, create a trend line, and calculate the equation of the trend line.
    • Calculate and interpret the correlation coefficient for a set of paired data.
    • Use the results of the regression line equation for predictions.
    • Solve real world applications.

    Hypothesis Testing

    • Discuss how confidence intervals relate to hypothesis testing.
    • Use the P value approach to test a hypothesis.
    • Perform the 5 steps in hypothesis testing with one-and two-tailed z-tests.
    • Perform the 5 steps in hypothesis testing with one-and-two- tailed "t" tests.
    • Discuss possible type 1 and type 2 errors in hypothesis testing.


    • Use statistics to analyze application problems.
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