Ancillary materials for interactive statistics:

1: Random Number Generator
2: Completing a Frequency, Relative, and Cumulative Relative Frequency Table Activity
3: The Box Plot Creation Game
4: Online Calculator of the Mean and Median
5: Online Mean, Median, and Mode Calculator From a Frequency Table
6: Standard Deviation Calculator
7: Guess the Standard Deviation Game
8: Mean and Standard Deviation for Grouped Frequency Tables Calculator
9: Z-Score Calculator
10. Expected Value and Standard Deviation Calculator
11: Be the Player Or the Casino Expected Value Game
12: Binomial Distribution Calculator
13: Normal Probability Calculator
14: Calculator For the Sampling Distribution for Means
15: Discover the Central Limit Theorem Activity
16: Sampling Distribution Calculator for Sums
17: Observe the Relationship Between the Binomial and Normal Distributions
18: Confidence Interval Calculator for a Mean Calculator With Statistics (Sigma Unknown)
19: Visually Compare the Student's t Distribution to the Normal Distribution
20: Sample Size for a Mean Calculator
21: Confidence Interval for a Mean (With Data) Calculator
22: Interactively Observe the Effect of Changing the Confidence Level and the Sample Size
23: Confidence Interval for a Mean (With Statistics) Calculator
24: Confidence Interval Calculator for a Population Mean (With Data, Sigma Unknown)
25: Confidence Interval For Proportions Calculator
26: Needed Sample Size for a Confidence Interval for a Population Proportion Calculator
27: Hypothesis Test for a Population Mean Given Statistics Calculator
28: Hypothesis Test for a Population Mean With Data Calculator
29: Hypothesis Test for a Population Proportion Calculator
30: Two Independent Samples With Data Hypothesis Test and Confidence Interval Calculator
31: Two Independent Samples With Statistics and Known Population Standard Deviations Hypothesis Test and Confidence Interval Calculator
32: Two Independent Samples With Statistics Calculator
33: Hypothesis Test and Confidence Interval Calculator: Difference Between Population Proportions
34: Hypothesis Test and Confidence Interval Calculator for Two Dependent Samples
35: Visualize the Chi-Square Distribution
36: Chi-Square Goodness of Fit Test Calculator
37: Chi-Square Test For Independence Calculator
38: Chi-Square Test For Homogeneity Calculator
39: Scatter Plot Calculator
40: Scatter Plot, Regression Line, r,and r^2 Calculator
41: Full Regression Analysis Calculator
42: Shoot Down Money at the Correct Correlation Game
43: Visualize How Changing the Numerator and Denominator Degrees of Freedom Changes the Graph of the F-Distribution
44: ANOVA Calculator
45: Central Limit Theorem Activity

This course covers descriptive statistics, the foundation of statistics, probability and random distributions, and the relationships between various characteristics of data. Upon successful completion of the course, the student will be able to: Define the meaning of descriptive statistics and statistical inference; Distinguish between a population and a sample; Explain the purpose of measures of location, variability, and skewness; Calculate probabilities; Explain the difference between how probabilities are computed for discrete and continuous random variables; Recognize and understand discrete probability distribution functions, in general; Identify confidence intervals for means and proportions; 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; Compute regression equations for data; Use regression equations to make predictions; Conduct and interpret ANOVA (Analysis of Variance). (Mathematics 121; See also: Biology 104, Computer Science 106, Economics 104, Psychology 201)

Natural Resources Biometrics begins with a review of descriptive statistics, estimation, and hypothesis testing. The following chapters cover one- and two-way analysis of variance (ANOVA), including multiple comparison methods and interaction assessment, with a strong emphasis on application and interpretation. Simple and multiple linear regressions in a natural resource setting are covered in the next chapters, focusing on correlation, model fitting, residual analysis, and confidence and prediction intervals. The final chapters cover growth and yield models, volume and biomass equations, site index curves, competition indices, importance values, and measures of species diversity, association, and community similarity.

Welcome to behavioral statistics, a statistics textbook for social science majors!

Table of Contents
Unit 1: Description
1: Introduction to Behavioral Statistics
2: What Do Data Look Like? (Graphs)
3: Descriptive Statistics
4: Distributions
5: Using z
6: APA Style
Unit 2: Mean Differences
7: Inferential Statistics and Hypothesis Testing
8: One Sample t-test
9: Independent Samples t-test
10: Dependent Samples t-test
11: BG ANOVA
12: RM ANOVA
13: Factorial ANOVA (Two-Way)
Unit 3: Relationships
14: Correlations
15: Regression
16: Chi-Square
Unit 4: Wrap Up
17: Wrap Up

The R Project for statistical computing (R) is a programming language and environment for statistics and graphing. Another commonly used programming language for statistics and data mining is Python. Both Python and R are easy to learn. If the primary purpose is statistical analysis, then R is usually preferred.Why learn/teach R? One of the major reasons why R is becoming more popular (TIOBE,2018) is that it is an open-source (i.e. free) software. Also, when dealing with a large number of variables, multiple datasets, and large samples, R is also a more efficient tool than traditional drop-down menu software such as SPSS. Finally, R programming is now very easy to use with the development of helpful packages.This open text will introduce R packages and step-by-step codes for conducting common statistical analyses in psychological research and classrooms. Funding acknowledgment: The author would like to thank the Society for the Teaching of Psychology (STP), American Psychological Association Division 2 Instructional Resource Award for their generous support of this project. This resource is licensed under the Creative Commons Attribution-ShareAlike4.0 International license (CC BY-SA4.0)