I. General Information
1. Course Title:
Honors Introduction to Statistics
2. Course Prefix & Number:
MATH 1461
3. Course Credits and Contact Hours:
Credits: 4
Lecture Hours: 4
4. Course Description:
This course covers descriptive statistics, sampling, probability, probability distributions, normal probability distributions, estimates and sample sizes, hypothesis testing, correlation and regression, inferences of two samples, and process control. Much of the content of this course will involve independent learning with classroom lecture involving more indepth involvement with statistical data. Students enrolled in this course will be required to do additional reading of statistical writings, participate in group projects, present projects to the class, and develop an original survey. Daily assignments will involve use of online homework to accompany the readings from the course. A student must be accepted into the honors program prior to registration.
5. Placement Tests Required:
Accuplacer (specify test): 
College Level Math 
Score: 
50 
Other (specify test): 
ACT 
Score: 
18

6. Prerequisite Courses:
MATH 1461  Honors Introduction to Statistics
Applies to all requirements
Accuplacer college level math score of 50 or higher, or MATh 1505 or MATH 1506, and Admission to the Honors Program
7. Other Prerequisites
Admission to the Honors Program
8. Prerequisite (Entry) Skills:
Arithmetic skills with whole numbers, integers, fractions/ratios, percentages and decimals.
Algebraic skills with linear & quadratic functions and equation manipulation.
9. Corequisite Courses:
MATH 1461  Honors Introduction to Statistics
There are no corequisites for this course.
II. Transfer and Articulation
1. Course Equivalency  similar course from other regional institutions:
Name of Institution

Course Number and Title

Credits

Bemidji State University

MATH2610 Applied Statistics

4

Normandale Community College

MATH1080 Introduction to Statistics

4

III. Course Purpose
2. MN Transfer Curriculum (General Education) Courses  This course fulfills the following goal area(s) of the MN Transfer Curriculum:
 Goal 2 – Critical Thinking
 Goal 4 – Mathematical/Logical Reasoning
IV. Learning Outcomes
1. CollegeWide Outcomes
CollegeWide Outcomes/Competencies 
Students will be able to: 
Demonstrate oral communication skills 
Presentation of projects, effectively demonstrating the use of statistical concepts. 
Demonstrate written communication skills 
Written documentation to accompany studies that clearly outline all processes used in the project. 
Demonstrate reading and listening skills 
Online homework and quizzes that will be completed prior to class. 
Demonstrate interpersonal communication skills 
Group work involving project development. 
Analyze and follow a sequence of operations 
Give detailed demonstration of how each stage of a study is developed and the data analyzed. 
Apply abstract ideas to concrete situations 
Students will take raw data and develop descriptive and inferential deductions based on that data. 
Utilize appropriate technology 
Students will use a graphing calculator to input statistical functions. 
2. Course Specific Outcomes  Students will be able to achieve the following measurable goals upon completion of
the course:
Expected Outcome

MnTC Goal Area

Compute measures of center, zscores, quartiles, and percentile ranks from data and give interpretations of these numerical measures

4b

Construct graphical representations of data and estimate common numerical measures from them

2a, 4b

Calculate basic probabilities

4d

Use binomial distributions to determine characteristics of data

4d

Apply normal approximation to estimate projected outcomes and percentiles for data that is normally distributed

4b,d

Compute and interpret confidence intervals and sample sizes for means, proportions, and variances

2a, c; 4a,b,c,d

Perform hypothesis testing for claims about proportions, means, and variations and interpret the results of these tests

4b,d

Develop inferences about two proportions, two means and dependent samples.

4d

Compute and interpret the correlation coefficient as a measure of the strength of the linear association between two numeric values

4a,b,d

Apply regression methods to estimate dependent variable values/interpret slope and constant in regression equations

4a,b,d

Conduct goodnessoffit test to determine correlations

4b,c,d

Perform analysis of variance

2a,c; 4a,b,c,d

V. Topical Outline
Listed below are major areas of content typically covered in this course.
1. Lecture Sessions
Lecture Content Outline

Introduction to Statistics

Summarizing and Graphing Data

Describe and compare data in statistical terms

Probability

Discrete Probability Distributions

Normal Probability Distributions

Estimates and Sample Sizes

Hypothesis Testing

Inferences from two samples

Correlation

Linear Regression

Goodnessoffit and Contingency Tables

Analysis of Variance


I. General Information
1. Course Title:
Honors Introduction to Statistics
2. Course Prefix & Number:
MATH 1461
3. Course Credits and Contact Hours:
Credits: 4
Lecture Hours: 4
4. Course Description:
This course covers descriptive statistics, sampling, probability, probability distributions, normal probability distributions, estimates and sample sizes, hypothesis testing, correlation and regression, inferences of two samples, and process control. Much of the content of this course will involve independent learning with classroom lecture involving more indepth involvement with statistical data. Students enrolled in this course will be required to do additional reading of statistical writings, participate in group projects, present projects to the class, and develop an original survey. Daily assignments will involve use of online homework to accompany the readings from the course. A student must be accepted into the honors program prior to registration.
5. Placement Tests Required:
Accuplacer (specify test): 
College Level Math 
Score: 
50 
Other (specify test): 
ACT 
Score: 
18

6. Prerequisite Courses:
MATH 1461  Honors Introduction to Statistics
Applies to all requirements
Accuplacer college level math score of 50 or higher, or MATh 1505 or MATH 1506, and Admission to the Honors Program
7. Other Prerequisites
Admission to the Honors Program
8. Prerequisite (Entry) Skills:
Arithmetic skills with whole numbers, integers, fractions/ratios, percentages and decimals.
Algebraic skills with linear & quadratic functions and equation manipulation.
9. Corequisite Courses:
MATH 1461  Honors Introduction to Statistics
There are no corequisites for this course.
II. Transfer and Articulation
1. Course Equivalency  similar course from other regional institutions:
Name of Institution

Course Number and Title

Credits

Bemidji State University

MATH2610 Applied Statistics

4

Normandale Community College

MATH1080 Introduction to Statistics

4

III. Course Purpose
2. MN Transfer Curriculum (General Education) Courses  This course fulfills the following goal area(s) of the MN Transfer Curriculum:
 Goal 2 – Critical Thinking
 Goal 4 – Mathematical/Logical Reasoning
IV. Learning Outcomes
1. CollegeWide Outcomes
CollegeWide Outcomes/Competencies 
Students will be able to: 
Demonstrate oral communication skills 
Presentation of projects, effectively demonstrating the use of statistical concepts. 
Demonstrate written communication skills 
Written documentation to accompany studies that clearly outline all processes used in the project. 
Demonstrate reading and listening skills 
Online homework and quizzes that will be completed prior to class. 
Demonstrate interpersonal communication skills 
Group work involving project development. 
Analyze and follow a sequence of operations 
Give detailed demonstration of how each stage of a study is developed and the data analyzed. 
Apply abstract ideas to concrete situations 
Students will take raw data and develop descriptive and inferential deductions based on that data. 
Utilize appropriate technology 
Students will use a graphing calculator to input statistical functions. 
2. Course Specific Outcomes  Students will be able to achieve the following measurable goals upon completion of
the course:
Expected Outcome

MnTC Goal Area

Compute measures of center, zscores, quartiles, and percentile ranks from data and give interpretations of these numerical measures

4b

Construct graphical representations of data and estimate common numerical measures from them

2a, 4b

Calculate basic probabilities

4d

Use binomial distributions to determine characteristics of data

4d

Apply normal approximation to estimate projected outcomes and percentiles for data that is normally distributed

4b,d

Compute and interpret confidence intervals and sample sizes for means, proportions, and variances

2a, c; 4a,b,c,d

Perform hypothesis testing for claims about proportions, means, and variations and interpret the results of these tests

4b,d

Develop inferences about two proportions, two means and dependent samples.

4d

Compute and interpret the correlation coefficient as a measure of the strength of the linear association between two numeric values

4a,b,d

Apply regression methods to estimate dependent variable values/interpret slope and constant in regression equations

4a,b,d

Conduct goodnessoffit test to determine correlations

4b,c,d

Perform analysis of variance

2a,c; 4a,b,c,d

V. Topical Outline
Listed below are major areas of content typically covered in this course.
1. Lecture Sessions
Lecture Content Outline

Introduction to Statistics

Summarizing and Graphing Data

Describe and compare data in statistical terms

Probability

Discrete Probability Distributions

Normal Probability Distributions

Estimates and Sample Sizes

Hypothesis Testing

Inferences from two samples

Correlation

Linear Regression

Goodnessoffit and Contingency Tables

Analysis of Variance

