Introduction To Statistics (Full Course)

What you'll learn
Express statistical information using proper terminology and graphs
Calculate measures of central tendency and dispersion
Interpret measures of central tendency and dispersion
Calculate probabilities and statistical measures
Perform sampling techniques
Determine appropriate probability models for given situations
Estimate parameters based on samples
Perform hypothesis testing
Analyze contingency tables using chi square technique
Determine linear relationship using regression and correlation
Use one-way ANOVA
Requirements
Basic Algebra Skills are needed for learning Statistics
Description
An overview of the ideas and concepts that are basic to modern statistics. Topics include descriptive statistics, probability, estimation, hypothesis testing, and linear regression. Students will be exposed to applications from a variety of fields.This course focuses on statistical reasoning and the solving of problems using real-world data rather than on computational skills. Emphasis is on interpretation and evaluation of statistical results that arise from simulation and technology-based computations using technology more advanced than a basic scientific calculator, such as graphing calculators with a statistical package, spreadsheets, or statistical computing software. Topics must include data collection processes (observational studies, experimental design, sampling techniques, bias), descriptive methods using quantitative and qualitative data, bivariate data, correlation, and least squares regression, basic probability theory, probability distributions (normal distributions and normal curve, binomial distribution), confidence intervals and hypothesis tests using p-values.This is a college entry statistics course, where any student can take this as long as you have basic algebra skills. AP Statistics students could also take this course to review all the basic concepts.There is one chapter on Probability, and it covers all the basics principle of probabilities needed for 1st semester statistics.We use TI Graphing Calculator to calculate all the statistics formulas in this course.Upon successful completion of this course, the student should be able to do the followingroduce and interpret descriptive statistics, graphically, numerically, and in tabular format.Calculate and interpret probability using union and intersection rules.Explain the concepts of random variable and distribution.Use technology to calculate probabilities with the normal and binomial distributions.Produce a confidence interval estimate from a given sample.Explain the rationale of hypothesis testing.Carry out, with the aid of technology, a variety of hypothesis tests, including z-tests and t-tests and interpret the meaning of the results.Use correlation analysis to determine the strength of a linear relationship between bivariate data and apply linear regression to describe this relationship.
Overview
Section 1: Chapter 1: Sampling and Data
Lecture 1 Sampling and Data
Section 2: Chapter 2: Displaying Data
Lecture 2 Displaying Data
Section 3: Chapter 3: Numerical Descriptors
Lecture 3 Numerical Descriptors
Section 4: Chapter 4: Probability Topics
Lecture 4 Probability Topics
Section 5: Chapter 5: Discrete Random Variables
Lecture 5 Discrete Random Variables
Section 6: Chapter 6: Continuous Random Variables
Lecture 6 Continuous Random Variables
Section 7: Chapter 7: Normal Distribution
Lecture 7 Normal Distribution
Section 8: Chapter 8: The Central Limit Theorem
Lecture 8 The Central Limit Theorem
Section 9: Chapter 9: Confidence Intervals
Lecture 9 Confidence Intervals
Section 10: Chapter 10: Hypothesis Testing with One Sample
Lecture 10 Chapter 10: Hypothesis Testing with One Sample
Section 11: Chapter 11: Hypothesis Testing with Two Sample
Lecture 11 Chapter 11: Hypothesis Testing with Two Samples
Section 12: Chapter 12: The Chi-Square Distribution Continued
Lecture 12 Chapter 12: The Chi-Square Distribution Continued
Section 13: Chapter 13: Linear Regression and Correlation
Lecture 13 Chapter 13: Linear Regression and Correlation
Section 14: Chapter 14: F-Distribution and One-Way Anova
Lecture 14 Chapter 14: F-Distribution and One-Way Anova
This course is perfect for anyone that needs to take Statistics or Probability in College/High School.


Homepage