mth231 | undergraduate
Statistics For The Life Sciences
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Collecting, Organizing, and Summarizing Data
- Calculate the mean, median, mode, standard deviation, variance, and z scores for a data set.
- Differentiate between populations and samples.
- Explain how random sampling is important in collecting statistical data.
- Differentiate among scatterplots, histograms, and frequency distributions.
Probabilities and Discrete Probability Distributions
- Calculate probability using the addition rule and the multiplication rule.
- Distinguish between independent and dependent events.
- Explain absolute risk reduction, relative risk, number needed to treat, odds ratios, and rates.
- Determine whether a procedure results in a binomial distribution or a Poisson distribution.
Normal Probability Distributions
- Describe normal distribution, standard normal distribution, and uniform distribution.
- Calculate the probability for a range of values in a normal distribution and in a standard normal distribution.
- Explain the central limit theorem.
- Describe point estimates, confidence intervals, confidence levels, critical values, and margins of error.
Confidence Intervals, Inferences, and Hypothesis Testing
- Interpret a confidence interval for an estimate of population mean and population variance.
- Differentiate among the z distribution, the t distribution, and the chi-square distribution.
- Describe hypotheses, hypothesis tests, null hypotheses, alternative hypotheses, test statistics, and significance levels.
- Differentiate between Type I and Type II errors.
Hypothesis Testing and Correlation
- Differentiate among the traditional method, the p -value method, and the confidence interval method of testing a claim about a proportion.
- Apply inferential statistics to test a claim about population mean and population standard deviation.
- Explain the use of the F distribution to compare variation in two samples.
- Interpret the correlation coefficient between two samples.
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