Introduction to Statistics
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In this course, students will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge. Students will learn about how statistics and probability work together. The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.After finishing this course, students should be comfortable evaluating an author's use of data and be able to extract information from articles and display that information effectively. Students will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistics and the foundation of statistics, move onto probability and random distributions, the latter of which enables statisticians to work with several aspects of random events and their applications. Finally, students will examine a number of ways to investigate the relationships between various characteristics of data.
Note: In addition to links to the Saylor course content for Microbiology, students who enroll in MAT202 via StraighterLine are provided access to proprietary services and materials which comprise the full ACE credit recommendation. All Saylor content is available free at Saylor.org (no purchase necessary); Saylor receives no compensation for student use of the content.
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Content Rating 

It was confusing going to another college site to get the information.
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Introduction to statistics. Pretty basic college level math for students who cant get a class on campus
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Introduction to statistics. Pretty basic college level math for students who cant get a class on campus
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This course was difficult and the study material did not correlate well with the exams.
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This course was difficult and the study material did not correlate well with the exams.
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It was confusing going to another college site to get the information.
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This course is poorly organized, and the use of multiple texts with differing notations is at best confusing, and at worst contradictory. I was highly disappointed in my experience, and it's a miracle that I passed. I strongly suggest you do not take this course through Straighterline. Go to your local community college.
Content Rating Overall Rating 
This course is poorly organized, and the use of multiple texts with differing notations is at best confusing, and at worst contradictory. I was highly disappointed in my experience, and it's a miracle that I passed. I strongly suggest you do not take this course through Straighterline. Go to your local community college.
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Video helps a lot and make it easier to understand.
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Hard but manageable
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The course material and the material tested are not related. There's so many things on the test that we never covered. I felt prepared going into test and quizzes, but felt that only 80% materials on test were actually covered
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It was hard not having a knowledgeable point person to go to.
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I did not think that this course was well put together. The quizs and the final are completely different from one another.
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I did not think that this course was well put together. The quizs and the final are completely different from one another.
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very complete
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very complete
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Video helps a lot and make it easier to understand.
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Great course hard as heck finial exam, I forgot so much form the beginning of the course.
Content Rating Overall Rating 
Great course hard as heck finial exam, I forgot so much form the beginning of the course.
Content Rating Overall Rating 
Hard but manageable
Content Rating Overall Rating 
The course material and the material tested are not related. There's so many things on the test that we never covered. I felt prepared going into test and quizzes, but felt that only 80% materials on test were actually covered
Content Rating Overall Rating 
It was hard not having a knowledgeable point person to go to.
Content Rating Overall Rating
Course Objectives
Upon successful completion of this course, you will be able to:
 define the meaning of descriptive statistics and statistical inference, describe the importance of statistics, and interpret examples of statistics in a professional context;
 distinguish between a population and a sample;
 explain the purpose of measures of location, variability, and skewness;
 apply simple principles of probability;
 compute probabilities related to both discrete and continuous random variables;
 identify and analyze sampling distributions for statistical inferences;
 identify and analyze confidence intervals for means and proportions;
 compare and analyze data sets using descriptive statistics, parameter estimation, hypothesis testing;
 explain how the central limit theorem applies in inference;
 calculate and interpret confidence intervals for one population average and one population proportion;
 differentiate between type I and type II errors;
 conduct and interpret hypothesis tests;
 identify and evaluate relationships between two variables using simple linear regression; and
 use regression equations to make predictions.
Unit  Unit Title  Subunit Title  Objectives 
1  Statistics and Data 


2  Elements of Probability and Random Variables 


3  Normal Distributions and Sampling Distributions 


4  Estimation with Confidence Intervals 


5  Hypothesis Test 


6  Linear Regression 


7  Review 


Successful completion of College Algebra is recommended before taking Introduction to Statistics.
Important Terms
In this course, different terms are used to designate tasks:
 Practice Exercise: A nongraded set of problems that where skills discussed in a topic are practiced.
 Graded Quiz: A graded online assessment that is usually shorter than a graded exam.
 Graded Exam: A graded online assessment that is comprehensive.
 This course does not require a text. The primary resources for this course are listed below which are free, online materials.
 Rice University: David M. Lane et al.’s Online Statistics Education: An Interactive Multimedia Course of Study
 Introductory Statistics
 Missouri State University: David W. Stockburger’s Introductory Statistics: Concepts, Models, and Applications
StraighterLine provides a percentage score and letter grade for each course. A passing percentage is 70% or higher. If you have chosen a Partner College to award credit for this course, your final grade will be based upon that college's grading scale. Only passing scores will be considered by Partner Colleges for an award of credit.
There are a total of 1000 points in the course:
Unit  Assessment  Points Available 
1  Graded Quiz 1  500 across all Graded Quizzes (total) 
2  Graded Quiz 2  
4  Graded Quiz 3  
5  Graded Quiz 4  
6  Graded Quiz 5  
7  Final Graded Exam  500 
Total  1000 
Final Proctored Exam
The final exam is developed to assess the knowledge you learned taking this course. All students are required to take an online proctored final exam in order complete the course and be eligible for transfer credit.
In this course, students will look at the properties behind the basic concepts of probability and statistics and focus on applications of statistical knowledge. Students will learn about how statistics and probability work together. The subject of statistics involves the study of methods for collecting, summarizing, and interpreting data.After finishing this course, students should be comfortable evaluating an author's use of data and be able to extract information from articles and display that information effectively. Students will also be able to understand the basics of how to draw statistical conclusions. This course will begin with descriptive statistics and the foundation of statistics, move onto probability and random distributions, the latter of which enables statisticians to work with several aspects of random events and their applications. Finally, students will examine a number of ways to investigate the relationships between various characteristics of data.
Note: In addition to links to the Saylor course content for Microbiology, students who enroll in MAT202 via StraighterLine are provided access to proprietary services and materials which comprise the full ACE credit recommendation. All Saylor content is available free at Saylor.org (no purchase necessary); Saylor receives no compensation for student use of the content.