 Searching Current Courses For Fall 2023 

Course: 
MAT 1260


Title:  Intro to Statistics: MA1 

Long Title:  Introduction to Statistics: GTMA1 

Course Description:  Introduces descriptive and inferential statistics, with an emphasis on critical thinking and statistical literacy. Topics include methods of data collection, presentation and summarization, introduction to probability concepts and distributions, and statistical inference of one and two populations. This course uses real world data to illustrate applications of a practical nature.
This is a statewide Guaranteed Transfer course in the GTMA1 category. 

Min Credit:  3 

Max Credit:  

Status Notes:  

 S: 

 S: 

Origin Notes:  ACC 

General Notes:  MPM Updates 3/28/2018 

General Notes:  updated new GT language 8/15/18 dl 
For REQUIRED SYLLABUS information that is to be included on all syllabi starting Spring 2018, 201830 go to https://internal.cccs.edu/wpcontent/uploads/documents/GTMA1RequiredSyllabusInfo.docx.
REQUIRED COURSE LEARNING OUTCOMES:
1. Communicate the language of statistics using the appropriate terminology.
2. Analyze numerical summaries and graphical displays of sample data.
3. Analyze bivariate data by applying the concepts of correlation and regression.
4. Apply the basic rules of probability.
5. Utilize the appropriate probability distribution.
6. Make inferences about one or more populations using sample data.
7. Utilize technology to further statistical understanding and reasoning.
RECOMMENDED TOPICAL OUTLINE:
I. The language and appropriate terminology of statistics
A. Introduction to experimental vs observational studies
B. Introduction to qualitative vs quantitative studies
C. Introduction to the research process
D. Introduction to sources of bias
E. Population vs samples
F. Parameters vs statistics
G. Types of data (discrete/continuous, quantitative/qualitative)
H. Types of variables (lurking/confounding/explanatory/response)
I. Sampling techniques (random/systematic/stratified/cluster/convenience)
J. Relevance of statistics to scientific and other realworld problems
II. Numerical summaries and graphical displays of sample data
A. Frequency distribution tables including construction
B. Graphical displays of qualitative and quantitative data including construction
C. Distribution shapes (modality and skew)
D. Measures of central tendency including calculations with or without technology
E. Measures of variation including calculations with or without technology
F. Measures of relative position including calculations with or without technology
III. Bivariate data by applying the concepts of correlation and regression
A. Scatter plots including construction
B. Correlation including calculations with or without technology
C. Linear regression
D. Analysis of residuals
IV. Fundamentals of probability
A. Law of Large Numbers
B. Addition and multiplication rules
C. Introduction to permutations and combinations
D. Complementary events
E. Conditional probability
V. Probability distribution
A. Introduction to discrete probability distributions
B. Binomial distributions
C. Normal distributions
VI. Inferences about one or more populations using sample data
A. The Central Limit Theorem
B. Sample size for mean and proportion
C. Confidence intervals for one and two populations
D. Hypothesis tests for one and two populations
E. Chisquare and goodness of fit tests
F. Introduction to Analysis of variance (ANOVA)
VII. Technology to further statistical understanding and reasoning

Arapahoe Community College 
ACC 

Community College of Aurora 
CCA 

Colorado Community College Sys 
CCCS 

Community College of Denver 
CCD 

Colorado Northwestern CC 
CNCC 

Front Range Community College 
FRCC 

Lamar Community College 
LCC 

Morgan Community College 
MCC 

Northeastern Junior College 
NJC 

Otero College 
OJC 

Pueblo Community College 
PCC 

Pikes Peak State College 
PPCC 

Red Rocks Community College 
RRCC 

Trinidad State College 
TSJC 
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