mth231 | undergraduate

Statistics For The Life Sciences

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This course will examine the concepts of statistics leading to the application of these concepts to the life sciences. Topics will include populations and samples, random sampling, probabilities, distributions, and confidence intervals.

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

Course details:

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

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    Standard Deviation, Probability, and Normal Distribution

    • Calculate probabilities using empirical vs. theoretical probability.
    • Calculate probabilities from statements involving AND and OR.
    • Use combinations to calculate the total number of possible events and calculate probability.
    • Calculate a probability from a Z-score and vice versa.
    • Calculate standard deviation and variance for ungrouped data.
    • Use the empirical rule to determine if a data value is usual or unusual.

    Central Limit Theorem and Estimates

    • Identify biased and unbiased estimators.
    • Use the Central Limit Theorem to calculate probabilities and Z-scores.
    • Calculate a probability from a T-score and vice versa.
    • Calculate and interpret confidence intervals for proportions and means.
    • Calculate the required sample size to estimate a population proportion and mean.

    Hypothesis Testing

    • Perform the five steps in hypothesis testing with one- and two-tailed "Z" tests.
    • Perform the five steps in hypothesis testing with one- and two- tailed "T" tests.

    Correlation and Regression

    • Interpret the correlation of data from a graph.
    • Calculate the correlation coefficient.
    • Perform a hypothesis test on a correlation coefficient.
    • Calculate the equation of the regression line for a set of paired data.
    • Use the results of the regression line equation for predictions.

    Introduction to Statistics, Graphing, and Measures of Center

    • Classify variables as categorical or qualitative.
    • Distinguish between a sample and a population.
    • Identify potential sources of bias in a sample.
    • Analyze a set of data with respect to characteristics such as Center, Distribution, Outliers, and Time.
    • Create a frequency distribution and histogram.
    • Create a graphical display of a sample using technology.
    • Use a graphical display of a sample to interpret characteristics such as Center, Distribution, Outliers, and Time.
    • Calculate mean, median, and mode for ungrouped data.
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