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CK-12 Advanced Probability and Statistics Concepts

Difficulty Level: Advanced Created by: CK-12
Table of Contents

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  • 1.

    An Introduction to Analyzing Statistical Data

    This chapter familiarizes students with data analysis. Related topics covered are classifying variables, measures of central tendency, and measures of spread.

  • 2.

    Visualizations of Data

    This chapter covers the many ways in which data can be displayed using histograms and frequency distributions.

  • 3.

    An Introduction to Probability

    This chapter introduces the student to the basic concepts of probability, including sample spaces and events, the additive and multiplicative rules, and permutations and combinations.

  • 4.

    Discrete Probability Distribution

    This chapter focuses on introducing students to probability distributions by covering random variables, discrete and continuous variables, and binomial and geometric distributions.

  • 5.

    Normal Distribution

    This chapter expands upon the previous lesson by covering the characteristics of standard normal probability distributions and some of their applications. The chapter considers the Empirical Rule, density curves, and utilizing real world data.

  • 6.

    Planning and Conducting an Experiment or Study

    This chapter covers in further detail the process of collecting data through studies and experiments. Topics considered are bias, experimental design, and randomization.

  • 7.

    Sampling Distributions and Estimations

    This chapter deals with survey analysis by considering probability samplings, confidence intervals, and the Central Limit theorem.

  • 8.

    Hypothesis Testing

    This chapter deals with hypothesis testing for proportions and means, the Student's t-distribution, and two sample hypothesis testing.

  • 9.

    Regression and Correlation

    This chapter allows students to use correlation and regression coefficients in order to determine linear relationships between bivariate data.

  • 10.

    Chi-Square

    This chapter introduces students to variance and the two Chi-Square tests: the Goodness-of-Fit test and the Test for Independence.

  • 11.

    Analysis of Variance and the F-Distribution

    This chapter expands upon the previous lesson’s introduction to variance, focusing on examining the f-max test and one- and two-way ANOVA tests.

  • 12.

    Non-Parametric Statistics

    This chapter concludes the course by introducing a series of tests that are utilized in non-parametric situations, including: the sign test, rank sum test, Kruskal Wallis test, runs test, and sign rank test.

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Description
Difficulty Level:
Advanced
Grades:
Date Created:
Aug 13, 2012
Last Modified:
Jun 20, 2016
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