Contents
Catalog Links

MAT 256 Statistics II

Statistics II explores advanced statistical concepts. Students are expected to build on introductory statistical reasoning. Students will apply concepts of hypothesis testing of means and proportions, chi-square tests, analysis of variance, multivariate linear regression, nonparametric testing methods, and statistical process control. Topics include techniques of applied problem-solving using data analysis software such as Excel.

Credits

3

Prerequisite

Prerequisite: MAT 255 or MAT 162

See Course Syllabus

Course Number and Title:

MAT 256 Statistics II

Campus Location

  • Georgetown
  • Dover
  • Stanton
  • Wilmington

Effective Date

202551

Prerequisites

Prerequisite: MAT 255 or MAT 162

Course Credits and Hours

3 credit(s)

3 lecture hours/week

1 lab hours/week

Course Description

Statistics II explores advanced statistical concepts. Students are expected to build on introductory statistical reasoning. Students will apply concepts of hypothesis testing of means and proportions, chi-square tests, analysis of variance, multivariate linear regression, nonparametric testing methods, and statistical process control. Topics include techniques of applied problem-solving using data analysis software such as Excel.

Additional Materials

None

Required Text(s)

Obtain current textbook information by viewing the campus bookstore - https://www.dtcc.edu/bookstores online or visit a campus bookstore. Check your course schedule for the course number and section.

Disclaimer

None

Core Course Performance Objectives (CCPOs)

  1. Evaluate population parameters using inferential statistics. (CCC 2, 6)
  2. Evaluate analysis of variance (ANOVA). (CCC 2, 6)
  3. Evaluate Chi-Square tests. (CCC 2, 6)
  4. Evaluate non-parametric tests. (CCC 2, 6)
  5. Evaluate data using graphical and numerical methods to study patterns and departures from patterns. (CCC 2, 6)
  6. Evaluate principals of statistical process control. (CCC 2, 6)
  7. Evaluate statistical analysis of time series data. (CCC 2,6)

See Core Curriculum Competencies and Program Graduate Competencies at the end of the syllabus. CCPOs are linked to every competency they develop.

Measurable Performance Objectives (MPOs)

Upon completion of this course, the student will:

  1. Evaluate population parameters using inferential statistics.
    1. Differentiate between point and interval estimates.
    2. Construct confidence intervals for population means and proportions.
    3. Determine the sample needed for the estimate of means and proportions.
    4. Conduct and interpret hypothesis tests for one mean.
    5. Conduct and interpret hypothesis tests for two means.
    6. Conduct and interpret hypothesis tests for one proportion.
    7. Conduct and interpret hypothesis tests for two proportions.
  2. Evaluate analysis of variance (ANOVA).
    1. Explain the underlying assumptions for ANOVA model.
    2. Conduct and interpret one-way ANOVA tests for the equality of three or more means.
    3. Conduct and interpret pairwise comparison of means.
    4. Conduct and interpret two-factor ANOVA tests using the randomized block design.
  3. Evaluate Chi-square tests.
    1. Conduct and interpret chi-square goodness of fit tests.
    2. Conduct and interpret chi-square tests for independence.
    3. Conduct and interpret chi-square tests for homogeneity.
  4. Evaluate non-parametric tests.
    1. Explain the advantages and disadvantages of non-parametric methods.
    2. Apply and interpret Spearman's rank correlation to test hypotheses.
    3. Apply and interpret the Wilcoxon signed-rank coefficient to test hypotheses.
    4. Apply and interpret the Wilcoxon rank-sum coefficient to test hypotheses.
  5. Evaluate data using graphical and numerical methods to study patterns and departures from patterns.
    1. Construct scatter plots for two variables.
    2. Calculate the regression equation using the least squares method.
    3. Obtain a point estimate of the dependent variable from the equation of the regression.
    4. Calculate and explain the correlation coefficient and the coefficient of determination.
    5. Perform residual analysis to determine the mean square error.
    6. Use appropriate technology to perform the calculations needed for regression analysis and interpret the results.
    7. Determine the regression equation for a dependent and two or more independent variables.
    8. Conduct and interpret a global test of significance of the regression equation using the F-test.
    9. Conduct and interpret individual tests of significance of the regression coefficients using the T-test.
  6. Evaluate principles of statistical process control.
    1. Construct and interpret R and x̄ charts for changes in variation and mean of process data.
    2. Construct and interpret P charts for changes in proportions of attributes.
  7. Evaluate statistical analysis of time series data.
    1. Define and interpret trend, cyclical, seasonal, and irregular components of time series.
    2. Calculate seasonal indices of time series by the ratio to moving average method.
    3. Use seasonal indices to provide forecasts.

Evaluation Criteria/Policies

The grade will be determined using the Delaware Tech grading system:

90-100 = A
80-89 = B
70-79 = C
0-69 = F
Students should refer to the Catalog/Student Handbook for information on the Academic Standing Policy, the Academic Integrity Policy, Student Rights and Responsibilities, and other policies relevant to their academic progress.

Final Course Grade

Calculated using the following weighted average

Evaluation Measure

Percentage of final grade

Summative: Tests (equally weighted)

40%

Summative: Projects (equally weighted)

40%

Formative: Homework

10%

Formative: Activities

10%

TOTAL

100%

Core Curriculum Competencies (CCCs are the competencies every graduate will develop)

  1. Apply clear and effective communication skills.
  2. Use critical thinking to solve problems.
  3. Collaborate to achieve a common goal.
  4. Demonstrate professional and ethical conduct.
  5. Use information literacy for effective vocational and/or academic research.
  6. Apply quantitative reasoning and/or scientific inquiry to solve practical problems.

Students in Need of Accommodations Due to a Disability

We value all individuals and provide an inclusive environment that fosters equity and student success. The College is committed to providing reasonable accommodations for students with disabilities. Students are encouraged to schedule an appointment with the campus Disabilities Support Counselor to request an accommodation needed due to a disability. The College's policy on accommodations for persons with disabilities can be found in the College's Guide to Requesting Academic Accommodations and/or Auxiliary Aids Students may also access the Guide and contact information for Disabilities Support Counselors through the Student Resources web page under Disabilities Support Services, or visit the campus Advising Center.

Minimum Technology Requirements

Minimum technology requirements for online, hybrid, video conferencing and web conferencing courses.

Academic Integrity

https://dtcc.smartcatalogiq.com/Current/Catalog/Academics/Academic-Integrity

Attendance

https://dtcc.smartcatalogiq.com/Current/Catalog/Search?q=attendance

Cell phone/Electronic Device

https://dtcc.smartcatalogiq.com/Current/Catalog/Student-Policy/Cell-Phone-and-Electronic-Device-Policy

Tuition Adjustment Policy

https://dtcc.smartcatalogiq.com/Current/Catalog/Financial/Tuition-Fee-Adjustment-Policy-Course-or-Semester-Withdrawal