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Statistics For The Life Sciences –
mth231
(3 credits)
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 Advisor.
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Hypothesis Testing and Correlation
- Interpret the correlation coefficient between two samples.
- Explain the use of the F distribution to compare variation in two samples.
- Apply inferential statistics to test a claim about population mean and population standard deviation.
- Differentiate among the traditional method, the p-value method, and the confidence interval method of testing a claim about a proportion.
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Confidence Intervals, Inferences, and Hypothesis Testing
- Differentiate between Type I and Type II errors.
- Describe hypotheses, hypothesis tests, null hypotheses, alternative hypotheses, test statistics, and significance levels.
- Differentiate among the z distribution, the t distribution, and the chi-square distribution.
- Interpret a confidence interval for an estimate of population mean and population variance.
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Normal Probability Distributions
- Describe point estimates, confidence intervals, confidence levels, critical values, and margins of error.
- Explain the central limit theorem.
- Calculate the probability for a range of values in a normal distribution and in a standard normal distribution.
- Describe normal distribution, standard normal distribution, and uniform distribution.
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Probabilities and Discrete Probability Distributions
- Determine whether a procedure results in a binomial distribution or a Poisson distribution.
- Explain absolute risk reduction, relative risk, number needed to treat, odds ratios, and rates.
- Distinguish between independent and dependent events.
- Calculate probability using the addition rule and the multiplication rule.
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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 among scatterplots, histograms, and frequency distributions.
- Explain how random sampling is important in collecting statistical data.
- Differentiate between populations and samples.
- The University of Phoenix reserves the right to modify courses.
- While widely available, not all programs are available in all locations or in both online and on-campus formats. Please check with a University Enrollment Advisor.
- Transferability of credit is at the discretion of the receiving institution. It is the student’s responsibility to confirm whether or not credits earned at University of Phoenix will be accepted by another institution of the student’s choice.
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