Competency 1: The student will be able to demonstrate, basic knowledge of statistical terms.
Competency 2: The student will be able to describe, explore and compare data by:
 Constructing and interpreting frequency tables and graphs such as bar graphs, pie charts and stem and leaf plots.
 Computing and interpreting the measures of centrality: the mean, median, mode and midrange.
 Computing and interpreting the measures of dispersion: The range, variance and standard deviation.
Competency 3: The student will be able to apply the measures of position by:
 Computing zscores.
 Applying the Empirical Rule to the Normal Distribution.
 Applying the Chebyshev’s Rule to the NonNormal (or unknown) Distributions.
Competency 4: The student will be able to apply the counting principles by:
 Defining the Fundamental Counting Principle.
 Computing the possible outcomes of compound events.
 Computing Combinations and Permutations.
Competency 5: The student will have a working knowledge of basic probability theory, including being able to:
 Describe a sample space and an event.
 Calculate probabilities of simple, compound and conditional events.
Competency 6: With respect to random variables, the student will be able to:
 Distinguish between discrete and continuous random variables.
 Construct a probability distribution for a discrete random variable and be able to compute its mean and standard deviation.
 Compute probabilities for random variables having a binomial distribution.
 Compute probabilities for random variables having a normal distribution.
 Apply the Central Limit Theorem.
 Approximate the Binomial Probability using the Normal Distribution
Competency 7: The student will be able to construct confidence intervals, relative to:
 A single mean with population standard deviation known and unknown.
 A single proportion.
 The difference between two means.
Competency 8: The student will be able to apply hypothesis test procedures by:
 Identifying Type I and Type II errors.
 Identifying and interpreting pvalues.
 Testing a single mean for large or small samples.
 Testing the difference between two means.
 Testing a single proportion.
Competency 9: The student will have a basic understanding of how to deal with bivariate data, including:
 Being able to construct and interpret a scatterplot.
 Being able to compute and interpret the linear correlation coefficient.
