Introduction to Statistics

Course Content from Saylor
Course Number: MAT202
Download Course Syllabus
Overall Rating
Content Rating

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.

Coming Soon

3
college credits
Course Type Icon
Self Paced
Course Department Icon
Mathematics
Publisher Icon
26 Reviews
Overall Rating
Content Rating
  • 11/9/14 by kswoj
    It was confusing going to another college site to get the information.
    Content Rating
    Overall Rating
  • 10/30/14 by mrhembookings
    Introduction to statistics. Pretty basic college level math for students who cant get a class on campus
    Content Rating
    Overall Rating
  • 10/30/14 by mrhembookings
    Introduction to statistics. Pretty basic college level math for students who cant get a class on campus
    Content Rating
    Overall Rating
  • 9/28/14 by corinroth
    Content Rating
    Overall Rating
  • 9/28/14 by corinroth
    Content Rating
    Overall Rating
  • 9/28/14 by doctorajkeith
    This course was difficult and the study material did not correlate well with the exams.
    Content Rating
    Overall Rating
  • 9/28/14 by doctorajkeith
    This course was difficult and the study material did not correlate well with the exams.
    Content Rating
    Overall Rating
  • 9/24/14 by ajean013
    Content Rating
    Overall Rating
  • 9/24/14 by ajean013
    Content Rating
    Overall Rating
  • 9/11/14 by kswoj
    It was confusing going to another college site to get the information.
    Content Rating
    Overall Rating
  • 8/31/14 by rgarrett1031
    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
  • 8/31/14 by rgarrett1031
    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
  • 8/7/14 by henryvi
    Video helps a lot and make it easier to understand.
    Content Rating
    Overall Rating
  • 8/6/14 by Bdukes25.bd
    Hard but manageable
    Content Rating
    Overall Rating
  • 8/3/14 by susantsan
    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
  • 8/1/14 by marie.olson
    It was hard not having a knowledgeable point person to go to.
    Content Rating
    Overall Rating
  • 7/25/14 by schassberger.k
    I did not think that this course was well put together. The quizs and the final are completely different from one another.
    Content Rating
    Overall Rating
  • 7/25/14 by schassberger.k
    I did not think that this course was well put together. The quizs and the final are completely different from one another.
    Content Rating
    Overall Rating
  • 7/16/14 by jdwhiteside13
    very complete
    Content Rating
    Overall Rating
  • 7/16/14 by jdwhiteside13
    very complete
    Content Rating
    Overall Rating
  • 7/8/14 by henryvi
    Video helps a lot and make it easier to understand.
    Content Rating
    Overall Rating
  • 6/18/14 by jsilling
    Great course hard as heck finial exam, I forgot so much form the beginning of the course.
    Content Rating
    Overall Rating
  • 6/18/14 by jsilling
    Great course hard as heck finial exam, I forgot so much form the beginning of the course.
    Content Rating
    Overall Rating
  • 6/8/14 by Bdukes25.bd
    Hard but manageable
    Content Rating
    Overall Rating
  • 3/8/14 by susantsan
    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
  • 1/8/14 by marie.olson
    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

  • The Science of Statistics and Its Importance
  • Methods for Describing Data
  • Apply various types of sampling methods to data collection;
  • Create and interpret frequency tables;
  • display data graphically and interpret the following types of graphs: stem plots, histograms, and boxplots;
  • identify, describe, and calculate the following measures of the location of data: quartiles and percentiles;
  • identify, describe, and calculate the measures of the center of mean, median, and mode; and
  • Identify, describe, and calculate the following measures of the spread of data: variance, standard deviation, and range.

2

Elements of Probability and Random Variables  

  • Classical Probability Model
  • Random Variables
  • Understand and use the terminology of probability;
  • Determine whether two events are mutually exclusive and whether two events are independent;
  • Calculate probabilities using the addition Rules and multiplication rules;
  • Construct and interpret Venn diagrams;
  • Apply useful counting rules in the context of combinational probability;
  • Identify and use common discrete probability distribution functions;
  • Calculate and interpret expected values;
  • Identify the binomial probability distribution, and apply it appropriately;
  • Identify the Poisson probability distribution, and apply it appropriately.

3

Normal Distributions and Sampling Distributions

  • Normal Distributions
  • The Concept of Sampling Distributions
  • Sampling Distributions for Common Statistics  
  • Identify and use continuous probability density functions;
  • Identify the normal probability distribution, and apply it appropriately;
  • Apply the central theorem to approximate sampling distributions;
  • Describe the role of sampling distributions in inferential statistics;
  • Interpret and create graphs of a probability distribution for the mean and a discrete variable;
  • Describe a sampling distribution in terms of repeated sampling;
  • Compute the mean and standard deviation of the sampling distribution of the population;
  • Identify or approximate a sampling distribution based on the properties of the population;
  • Compare and evaluate the sampling distributions of different sample sizes; and
  • Compare and evaluate the performance of different estimators based on their sampling distributions.

4

Estimation with Confidence Intervals

  • Point Estimators and Their Characteristics
  • Confidence Intervals
  • Explain the central limit theorem, and use it to construct confidence intervals;
  • Compare t-distribution and normal distribution;
  • Apply and interpret the central limit theorem for sample averages;
  • Calculate and interpret confidence intervals for population averages and one population proportions; and
  • Interpret the student-t probability distribution as the sample size changes.

5

Hypothesis Test

  • Elements of Hypothesis Testing
  • Tests of Population Means  
  • Differentiate between type I and type II errors;
  • Describe hypothesis testing in general and in practice;
  • Interpret and explain how to conduct hypothesis tests for a single population mean and population proportion, when the population standard deviation is unknown;
  • Interpret and explain how to conduct hypothesis tests for a single population proportion; and
  • Classify hypothesis tests by type.

6

Linear Regression  

  • The Regression Model
  • Fitting the Model
  • Discuss basic ideas of linear regression and correlation;
  • Identify the assumptions that inferential statistics in regression are based on;
  • Compute the standard error of a slope;
  • Test a slope for significance;
  • Construct a confidence interval on a slope; and
  • Calculate and interpret the correlation coefficient.

7

Review

  • Review        
  • Review and Final Exam

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 non-graded 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.

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


You are required to take an online proctored final exam in order to be eligible for transfer credit. You can take your proctored final exam at home or anywhere you have access to a webcam with a microphone and a reliable, high-speed internet connection. For additional questions, please refer to the FAQ on Online Proctoring or contact your student advisors at 877-787-8375.

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.

Create your own custom Introduction to Statistics ! Select up to courses from the list below.

Introduction to Statistics   +$0.00
Tutoring   +$0.00

Subtotal
$25.00

plus subscription
Introduction to Statistics

Introduction to Statistics

$0.00

Your Courses

  • {{label}}:{{options}}
{{qty}} x {{name}}
{{qty}} x {{name}}
  •  
Plus Membership [?]

Only registered users can write reviews. Please, log in or register