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MATH 2453 - Statistics for Renewable Resources

Mathematics Part-time Studies Course

School of Computing and Academic Studies

Course Details

An introductory level course in statistics. Includes descriptive statistics; measures of central tendency, variation and skewness; probability laws and distributions; inferences from one and two samples; correlation and regression; estimation of sample size; hypothesis tests from large and small samples; estimation of parameters from various sampling designs. These methods are applied to examples chosen from the Renewable Resources field.

Prerequisite(s)

MATH 1451

Credits

5.0

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Learning Outcomes

Upon successful completion of this course, the student will be able to:

  • Demonstrate the application of statistical methods to problems of estimation and hypothesis testing in the Renewable Resources field.
  • Present an organized summary of the basic statistical properties of a data set, and draw appropriate conclusions from it regarding a related population.
  • Explain the meaning and importance of the underlying assumptions behind the statistical procedures commonly used in the Renewable Resources field.

To accomplish the above, the student will study and apply:

  • Various statistical charts including the stem and leaf plot, histogram, pareto chart, pie chart, box and whisker plot, and scatterplot.
  • Frequency distributions and grouped data; understand class limits, boundaries and marks.
  • Statistical measures including those of:
    • Central tendency: mean, median, mode, mid-range, weighted mean;
    • Position: quartiles, percentiles;
    • Variation: range, inter-quartile range, standard deviation, coefficient of variation;
    • And skewness.
  • Probability (independence, conditional probability, addition and multiplication rules, sample spaces).
  • Discrete probability distributions such as the binomial and Poisson distributions.
  • Sampling, randomness, the difference between a sample and a population, use random numbers to choose a sample.
  • Continuous probability distributions, such as the normal, t, and Chi-Squared distributions and use the applicable statistical tables, the normal approximation to the binomial distribution, central limit theorem.
  • Sampling methods, including:
    • Computation of sampling error and confidence limits, use of the finite population correction,
    • Estimation of sample size with and without the finite population correction.
  • Hypothesis testing for one- and two-sided alternatives. The cases studied are:
    • One and two sample tests for the mean and proportion,
    • Chi-Squared tests for independence and goodness-of-fit, contingency tables.
  • Linear regression and correlation techniques, compute and interpret linear regression and correlation coefficients from a set of data.
  • Statistical functions on an electronic calculator including means, standard deviations, sums and sums of squares.
  • Use spreadsheet and statistical software to do statistical data analysis.

Effective as of Fall 2014

Related Programs

MATH 2453 is offered as a part of the following programs:

School of Construction and the Environment

  1. Fish, Wildlife and Recreation
    Full-time   Diploma

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