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Co-Requisite Statistics
Subject: Mathematics
Book Language: English
Audience: High School, College
Book Cover: https://images.pexels.com/photos/2444429/pexels-photo-2444429.jpeg?auto=compress&cs=tinysrgb&dpr=2&w=500
Created date: June 3, 2021
Updated date: August 24, 2021
Target Release Date: 2022-05-31
License:
- No Rights Reserved
Needs:
- Editors
- Proofreaders
- Lead Authors
Description:
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Project Summary
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Short Description:
“Introduction to Statistics” prepares students to solve problems that involve collecting and analyzing data, and to make inferences and evaluate arguments that are based on data analysis in all fields of study. As such, the course will provide the student with the fundamental concepts and methods of analysis. The topics in this course include: descriptive statistics; inferential statistics; sample quantities; normal, binomial, hypergeometric, and Poisson distributions; sampling distributions; point and interval estimation; hypotheses testing; inferences about means, proportions, and deviations; tests for independence and goodness-of-fit; correlation and regression; and the development and use of all statistical tables needed for computations. The project will convert homegrown content to compile a set of ancillary materials for Topics of Introduction to Statistics. This course is the co-requisite course for Introduction to Statistics.
Outline
Collecting Data
1.1 The Structure of Data
1.2 Sampling from a Population
1.3 Experiments and Observational Studies
Describing Data
2.1 Categorical Variables
2.2 One Quantitative Variable: Shape and Center
2.3 One Quantitative Variable: Measures of Spread
2.4 Boxplots and Quantitative/Categorical Relationships
Probability
P.1. Probability Rules
P.2. Tree Diagrams
P.3. Combinations and Permutations
Distributions
P.3. Random Variables and Probability Functions
P.4. Binomial Probabilities
P.5. Normal Distribution
Sampling Distributions
Confidence Intervals
Single Proportion
Single Mean
Difference in Proportions
Difference in Means
Hypothesis Testing
6.1. Inference for a Proportion
6.2. Inference for a Mean
6.3. Inference for a Difference in
6.4. Inference for a Difference in Means
6.5. Paired Difference in Means
Chi Square
7.1. Testing Goodness-of-Fit for a Single Categorical Variable
7.2. Testing for an Association between Two Categorical Variables
ANOVA
Linear Regression
2.5 Two Quantitative Variables: Scatterplot and Correlation
2.6 Two Quantitative Variables: Linear Regression