mth463 | undergraduate

Applied Statistics

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This course surveys descriptive and inferential statistics with emphasis on practical applications of statistical analysis. The principles of collecting, analyzing, and interpreting data are covered. In addition, this course examines the role of statistical analysis, statistical terminology, the appropriate use of statistical techniques, and interpretation of statistical findings through the applications and functions of statistical methods.

This undergraduate-level course is 5 weeks This course is available to take individually or To enroll, speak with an Enrollment Representative.

Course details:

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

topic title goes here

    Summarizing Data

    • Calculate range, variance, and standard deviation for ungrouped data.
    • Create a graphical representation of data.
    • Develop a frequency distribution based on raw data.
    • Interpret a graphical representation of data.
    • Calculate mean, median, and mode for ungrouped data.

    Correlation and Regression

    • Develop a simple linear regression equation.
    • Predict the value of Y′ for a given value of X using a simple linear regression equation.
    • Determine the strength of the linear relationship between two variables.

    Probability

    • Compute and interpret probabilities.
    • Distinguish between the terms probability distribution and random variable .
    • Compute probabilities of a Poisson probability distribution.
    • Compute probabilities of binomial experiments.

    Probability Distribution

    • Describe the properties of the normal distribution.
    • Calculate probabilities for means and proportions based on a normal distribution using a z table.
    • Determine the appropriate confidence interval to construct.

    Introduction to Statistics

    • Distinguish among the types of data.
    • Distinguish observational studies with designed experiments.
    • Identify sampling methods.
    • Explain experiment design.
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