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Jason

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Brian

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Anatomy & Physiology

Bruce

College Algebra covers algebraic topics and skills necessary to succeed in college-level math

College Algebra

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Johnny

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Kylia

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Dive deep into General, Organic, and Biological Chemistry with videos, practice problems, and more.

Intro to Chemistry

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Cell Biology

Analytical Chemistry

Study topics incliding trogonometric functions, identities and equations, solutions of triangles, complex numbers, and other topics as time permits

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Callie

Learn the toughest concepts covered in Precalculus with step-by-step video tutorials and practice problems by world-class tutors

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Nick

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Business Statistics

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Nutrition

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Dive deep into Python with videos and more.

Introduction to Python

Arianne Dee

Agile Project and Product Management

Agile & Product Management

Mariya Breyther

Introduction to Microsoft Power BI

Microsoft Power BI

Chris Sorensen

Data Analysis Fundamentals with Excel

Data Analysis - Excel

Chris Sorensen & Ammul Shergill

Getting Started with  and Cryptocurrency

Introduction to Blockchain

George Levy

Learn Enough HTML, CSS and Layout to be Dangerous

HTML, CSS & Layout

Lee Donahoe & Michael Hartl

Learn Enough JavaScript to be Dangerous: A Tutorial Introduction to Programming with JavaScript

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Michael Hartl

R Programming

Jared P. Lander

Digital Marketing Analytics Beyond Advertising

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Mike Moran

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Jeffrey K. Pinto

AI in Marketing

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From probability to hypothesis testing, statistics concepts are explained step-by-step to build problem-solving skills and exam readiness.

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Patrick Ford

Callie Rethman

Colleen Daly

1. Intro to Stats and Collecting Data

2. Describing Data with Tables and Graphs

3. Describing Data Numerically

4. Probability

5. Binomial Distribution & Discrete Random Variables

6. Normal Distribution and Continuous Random Variables

7. Sampling Distributions & Confidence Intervals: Mean

8. Sampling Distributions & Confidence Intervals: Proportion

9. Hypothesis Testing for One Sample

10. Hypothesis Testing for Two Samples

11. Correlation

12. Regression

13. Chi-Square Tests & Goodness of Fit

14. ANOVA

[BOOK STATISTICS] DEFAULT

Justin

Sampling Distribution of Sample Proportion

Confidence Intervals for Population Proportion

Steps in Hypothesis Testing

Performing Hypothesis Tests: Means

Performing Hypothesis Tests: Proportions

Two Proportions

Two Means - Unknown, Unequal Variance

Two Means - Matched Pairs (Dependent Samples)

Scatterplots & Intro to Correlation

Correlation Coefficient

Linear Regression & Least Squares Method

Residuals

Coefficient of Determination

Prediction Intervals

Goodness of Fit Test

Contingency Tables

Independence Tests

Homogeneity Tests

Introduction to ANOVA

Statistics Final

A chi-square test produces a test statistic of χ2=3.281\chi^2=3.281. Should you reject the null hypothesis based on the graph given below? Note: The purple area indicates the rejection region.

A chi-square test produces a test statistic of $chi squared equals 3.281$ . Should you reject the null hypothesis based on the graph given below? Note: The purple area indicates the rejection region.