## Common Course Numbering System Searching Current Courses For Summer 2022

 Course: MAT 1260 Title: Intro to Statistics: MA1 Long Title: Introduction to Statistics: GT-MA1 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 GT-MA1 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

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.

REQUIRED 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 real-world 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
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.  Chi-square and goodness of fit tests
F.  Introduction to Analysis of variance (ANOVA)
VII.  Technology to further statistical understanding and reasoning

 Course Offered At:

 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 Junior College OJC Pueblo Community College PCC Pikes Peak Community College PPCC Red Rocks Community College RRCC Trinidad State Junior College TSJC 