Course Number and Title:
MAT 256 Statistics II
Campus Location
- Georgetown
- Dover
- Stanton
- Wilmington
Prerequisites
Prerequisite: MAT 255 or MAT 162
Course Credits and Hours
3 credit(s)
3 lecture hours/week
1 lab hours/week
Course Description
This course covers hypothesis testing of means and proportions, chi-square test, analysis of variance, regression and correlation analysis, non-parametric testing methods, and statistical process control. Topics include techniques of applied problem solving using data analysis software such as Excel.
Additional Materials
Graphing Calculator: TI 83 or TI 84
Disclaimer
Proctored testing is required for all tests, regardless of the course format. Online students may use any DTCC Testing Center at no additional charge. Additional fees may apply for virtual proctoring or testing at another location.
Core Course Performance Objectives (CCPOs)
- Calculate point and interval estimate of means and proportions. (CCC 2, 6)
- Perform tests of hypothesis on means and proportions. (CCC 2, 6)
- Apply analysis of variance (ANOVA) to test hypothesis on three or more means. (CCC 2, 6)
- Apply chi-square analysis to test the independence of two variables. (CCC 2, 6)
- Apply non-parametric testing methods to appropriate data. (CCC 2, 6)
- Employ correlation and simple regression to analyze the association between two variables. (CCC 2, 6)
- Apply multiple regression to analyze the relationship between the dependent and independent variables. (CCC 2, 6)
- Apply principals of statistical process control. (CCC 2, 6)
- Interpret and perform 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:
- Calculate point and interval estimate of means and proportions.
- Differentiate between point and interval estimates.
- Construct confidence interval for a population mean from a large sample, using the normal distribution.
- Construct confidence interval for a population mean from a small sample, using the T-distribution.
- Construct confidence interval for the proportion.
- Determine the sample needed for the estimate of means and proportions.
- Perform tests of hypothesis on means and proportions.
- Test hypothesis of one mean from a large sample.
- Test hypothesis of one mean from a small sample.
- Test hypothesis of two means from large samples.
- Test hypothesis of two means from small samples.
- Test hypothesis on one proportion.
- Test hypothesis on two proportions.
- Apply analysis of variance (ANOVA) to the hypothesis on three or more means.
- Explain the underlying assumptions for ANOVA model.
- Test for the equality of three or more means, using one-way ANOVA test.
- Perform pairwise comparison of means.
- Perform two-factor ANOVA tests using the randomized block design.
- Use appropriate technology to perform calculations needed for analysis of variance, and interpret the results.
- Apply chi-square analysis to test the independence of two variables.
- Test for the equality of three or more proportions.
- Test for the goodness of fit of an observed frequency distribution.
- Test for the independence of two variables from data.
- Use appropriate technology to perform calculations for chi-square tests, and interpret the results.
- Apply non-parametric testing methods to appropriate data.
- Explain the advantages and disadvantages of non-parametric methods.
- Use the Spearman's rank correlation to test hypothesis about a matched pair of observations.
- Use the Wilcoxon signed rank coefficient to test hypothesis about a matched pair of observations.
- Use the Wilcoxon rank sum coefficient to test hypothesis about independent variables.
- Employ correlation and simple regression to analyze the association between two variables.
- Construct scatter plots for two variables.
- Calculate the regression equation using the least squares method.
- Obtain a point estimate of the dependent variable from the equation of the regression.
- Calculate and explain the correlation coefficient and the coefficient of determination.
- Perform residual analysis to determine the mean square error.
- Use appropriate technology to perform the calculations needed for regression analysis and interpret the results.
- Apply multiple regression to analyze the relationship between the dependent and independent variables.
- Determine the regression equation for a dependent and two or more independent variables.
- Perform a global test of significance of the regression equation using the F-test.
- Perform individual tests of significance of the regression coefficients using the T-test.
- Use appropriate technology to perform multiple regression analysis, and interpret the results.
- Apply principals of statistical process control.
- Construct R and x̄„ charts for changes in variation and mean of process data.
- Construct P charts for changes in proportions of attributes.
- Interpret process control charts to determine statistical stability.
- Use appropriate technology to create and evaluate process control charts.
- Interpret and perform statistical analysis of time series data.
- Define and interpret trend, cyclical, seasonal, and irregular components of time series.
- Calculate seasonal indices of time series by the ratio to moving average method.
- 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
|
|
Tests (summative) (equally weighted)
|
40%
|
|
Projects (summative) (equally weighted)
|
40%
|
|
Homework (formative)
|
10%
|
|
Formative Assessments
|
10%
|
|
TOTAL
|
100%
|
Core Curriculum Competencies (CCCs are the competencies every graduate will develop)
- Apply clear and effective communication skills.
- Use critical thinking to solve problems.
- Collaborate to achieve a common goal.
- Demonstrate professional and ethical conduct.
- Use information literacy for effective vocational and/or academic research.
- 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.