Instructor: Wei Zhao Email: wzhao@mdc.edu

Course STA 2023 Statistical Methods
Reference # 572209
Credits 3
Text/Materials
 Required ISBN: N/AAuthor: Mario TriolaTitle: Course Compas for Elementary Statistics, 11th EditionPublisher: Pearson Supplemental ISBN: 0-321-570898Author: Mario TriolaTitle: Elementary Statistics w/ MyMathLab, 11th EditionPublisher: Pearson

Fee
 Florida Resident Distance Learning Fee VC Course Total \$354.66 \$45.00 \$399.66 Non Florida Resident Distance Learning Fee VC Course Total \$1,207.53 \$45.00 \$1,252.53
Prerequisites MAT1033.
Requirements All Virtual College courses require high-speed internet access. Microsoft Office applications such as Word, Excel, and PowerPoint are required. For ease of use when accessing either LMS, both PC and MAC users must use Mozilla Firefox as the default browser. Your course may appear to be functioning correctly in other browsers but some tools, assignments and assessments may not work in these other browsers. Don’t let your course work be affected by the wrong browser.
Description This course will introduce students to statistical methods. Students will learn topics to include collecting, grouping and presenting; measures of central tendency and dispersion; probability; testing hypotheses; confidence intervals; and correlation.
Course
Competencies

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:

1.  Constructing and interpreting frequency tables and graphs such as bar graphs, pie charts and stem and leaf plots.
2. Computing and interpreting the measures of centrality: the mean, median, mode and midrange.
3. 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:

1.  Computing z-scores.
2. Applying the Empirical Rule to the Normal Distribution.
3. Applying the Chebyshev’s Rule to the Non-Normal (or unknown) Distributions.

Competency 4:
The student will be able to apply the counting principles by:

1.  Defining the Fundamental Counting Principle.
2. Computing the possible outcomes of compound events.
3. Computing Combinations and Permutations.

Competency 5: The student will have a working knowledge of basic probability theory, including being able to:

1. Describe a sample space and an event.
2. Calculate probabilities of simple, compound and conditional events.

Competency 6:
With respect to random variables, the student will be able to:

1. Distinguish between discrete and continuous random variables.
2. Construct a probability distribution for a discrete random variable and be able to compute its mean and standard deviation.
3. Compute probabilities for random variables having a binomial distribution.
4. Compute probabilities for random variables having a normal distribution.
5. Apply the Central Limit Theorem.
6. Approximate the Binomial Probability using the Normal Distribution

Competency 7:
The student will be able to construct confidence intervals, relative to:

1. A single mean with population standard deviation known and unknown.
2. A single proportion.
3. The difference between two means.

Competency 8:
The student will be able to apply hypothesis test procedures by:

1. Identifying Type I and Type II errors.
2. Identifying and interpreting p-values.
3. Testing a single mean for large or small samples.
4. Testing the difference between two means.
5. Testing a single proportion.

Competency 9:
The student will have a basic understanding of how to deal with bivariate data, including:

1. Being able to construct and interpret a scatter-plot.
2. Being able to compute and interpret the linear correlation coefficient.