Statistics 101: Principles of Statistics

Let instructors in this statistics course show you how to summarize data and interpret a variety of tables and plots. Video lessons and quizzes can also teach you to conduct a probability experiment and solve statistical estimation problems. 

About This Course

Whether you'd like a refresher on the differences between descriptive and inferential statistics or are looking to hone your ability to analyze residuals, this course's video lessons have got you covered. Instructors discuss topics ranging from sample variance and box plots to conditional probabilities and z-scores. Areas of study addressed in this course include:

  • Statistical types, data models and levels of measurement
  • Methods for interpreting data tables and plots
  • Random sample types and sampling distributions
  • Uses of population parameters and confidence intervals
  • Problem solving with probability and linear regression
  • Theories and steps associated with hypothesis testing

If statistics lessons on confidence intervals and t-distributions sound a bit daunting, rest assured that our experienced instructors can walk you through the ins and outs of this discipline with plenty of graphical representations, examples and illustrations. Moreover, the video tags and transcripts allow you to quickly access lesson content covering difficult subjects as many times as you need. If you feel you'd also benefit from sample problems and review questions, there are self-assessment quizzes to help you out in this area as well.

Course Topics

Course Chapter Objectives
Overview of Statistics Learn to identify the differences between inferential and descriptive statistics and populations and parameters. Explore various data types and levels of measurement alongside methods for selecting experiment models. Get tips for recognizing biased or misleading uses of statistics.
Summarizing Data Find out how to calculate mean, median and mode and describe the shape of a data set. Study procedures for finding maximums, minimums, outliers and percentiles. Identify standard deviations and shifts in the mean as well as methods for ordering and ranking data.
Tables and Plots Discover joint, marginal and conditional frequencies and identify the differences between bivariate and univariate data. Determine how to interpret stem and leaf displays, histograms and frequency polygons as well as dot and box plots, bar graphs, pie charts and two-way tables. Use data to make predictions and calculate percent increase.
Probability Understand basic set theory and classical approaches to probability. Learn how to find the probability of simple, compound and complementary events as well as independent and dependent events. Observe how simple conditional probabilities can be applied to real-world scenarios.
Discrete Probability Distributions Practice graphing and interpreting discrete probability distributions used to find expected values. Examine binomial probabilities and learn to recognize properties of normal and binomial distributions.
Continuous Probability Distributions Learn to graph continuous probability distributions and find their expected values. Explore the uses of these distributions to estimate area and population percentages.
Sampling Explore simple, stratified, cluster and systematic random samples. Study the law of large numbers and discuss the central limit theorem, sampling distributions and sample means.
Statistical Estimation Identify the relationships between confidence intervals, sample size and sample means. Examine properties of the t-distribution and learn the differences between biased and unbiased estimators and point and interval estimation.
Hypothesis Testing Follow steps in hypothesis testing for small and large independent samples, matched pairs and proportions. Understand the differences between type I and type II errors.
Regression and Correlation Learn how to create and interpret scatterplots, solve problems using linear regression and analyze residuals. Practice finding the correlation coefficient and the coefficient of determination. Distinguish between correlation and causation and find out how to transform nonlinear data.

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Education Portal Instructors

Education Portal's 53 instructors bring a diverse array of experience and expertise to each course. From teaching philosophy in Athens, Greece, to exploring the mystery of genetics, each instructor is uniquely qualified to bring students the best online learning experience possible. Meet them now!

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