Complete 100 Level Stat Course - Introduction to Statistics
4.0
(3)
31 learners
What you'll learn
This course includes
- 16.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 107 lessons • 16.3 hours of video
Complete 100 Level Stat Course - Introduction to Statistics
107 lessons
• 16.3 hours
Complete 100 Level Stat Course - Introduction to Statistics
107 lessons
• 16.3 hours
- population vs sample 07:21
- parameter vs statistic 06:21
- Types of Data 07:30
- Levels of Measurement 11:52
- Sources of Data 08:13
- Common Misuses of Statistics 05:55
- Observational vs Experimental Study 05:28
- Types of Sampling 08:17
- Frequency Distributions 10:10
- Frequency Distributions class midpoints and class boundaries 08:02
- Histograms 06:49
- Relative Frequency Histogram 09:57
- Cumulative Frequency 05:27
- Normal Distribution Histogram 03:02
- Frequency Distribution for Nominal Data and Bar Graph 05:12
- Measures of Center - Introduction and Mean 07:23
- Measures of Center - Median 03:55
- Measures of Center - Mode 03:55
- Measures of Center - Midrange 02:36
- Measures of Center and Shapes of Distributions 04:08
- Determining the Mean from a Frequency Distribution 07:39
- Determining a weighted mean 04:55
- Measure of Variation - Introduction and Range 03:12
- Measures of Variation - Standard Deviation 10:05
- Measures of Variation - Variance 03:24
- Measures of Variation Coefficient of Variation 07:37
- Range Rule of Thumb 04:56
- Empirical Rule 06:54
- Chebyshevs Theorem 07:50
- Chebychevs Theorem Second Example 06:15
- Measures of Relative Standing - z scores 06:56
- Measures of Relative Standing - percentiles 08:21
- Measures of Relative Standing - Quartiles 08:22
- Measures of Variation using Quartiles and Percentiles 11:25
- Box Plot 07:48
- Outliers and the Modified Box Plot 10:45
- Sample Space and Tree Diagrams 07:55
- Probability Rules and Interpreting Probability 06:13
- Basic Rules for Computing Probability - Relative Frequency Approximation 09:40
- Basic Rules for Computing Probability - Classical Approach to Probability 05:47
- Basic Rules for Computing Probability - Subjective Probabilities 02:10
- Complement 05:23
- Calculating the Probability for At Least One 03:57
- Addition Rule 10:25
- Determine if Events are Disjoint 05:46
- More Examples of the Addition Rule 07:31
- Multiplication Rule 08:45
- More Examples of the Multiplication Rule 05:29
- Conditional Probability 06:55
- Another Example using the Conditional Probability Rule 03:33
- Definition of Random Variable and Probability Distribution 06:07
- Examples of Constructing the Probability Distribution Function 06:39
- Using Probability Distribution Functions to Calculate Probabilities 05:30
- Calculating the Mean or Expected Value of a Probability Distribution Function 05:23
- Calculating the Standard Deviation and Variance of a Discrete Probability Distribution Function 08:58
- Another Example Finding the Expected Value 05:18
- Introduction to the Binomial Probability Distribution Function 14:37
- More Binomial Probability Distribution Examples 11:51
- Another Binomial Probability Distribution Function Example 06:51
- Mean Standard Deviation and Variance of the Binomial Probability Distribution 08:02
- Introduction to the Density Curve 06:58
- Using Area Under the Density Curve to Determine Probability 08:46
- Another Example of Using the Area Under a Density Curve to Calculate Probabilities 07:03
- Introduction to the Normal Distribution 05:58
- Introduction to the Standard Normal Distribution 07:31
- Finding Probabilities for the Standard Normal Distribution 14:53
- Finding Z values when Provided with Probabilities 12:32
- Finding Probabilities for ANY Normal Distribution 15:29
- Finding X a normally distributed random variable when Provided with Probabilities 14:16
- Central Limit Theorem Finding Probabilities involving Sample Means 14:40
- Another Example of Finding Probabilities Involving Sample Means 09:31
- Introduction to Confidence Intervals 08:54
- Finding Standard Normal Critical Values 11:15
- Confidence Intervals for Population Proportion 15:49
- Another example of Calculating a Confidence Interval for Population Proportion 08:02
- Calculating Sample Size when Estimating Population Proportions 12:07
- Calculating a Confidence Interval for Population Mean when Sigma is Known 09:16
- Calculating Sample Size when Estimating Population Mean 06:31
- Finding t distribution Critical Values 04:50
- Calculating a Confidence Interval for Population Mean when Sigma is Unknown 10:19
- Introduction to Hypothesis Testing 18:39
- Left Tailed Hypothesis Test for Population Proportion 11:13
- Two Tailed Hypothesis Test for Population Proportion 09:42
- Right Tailed Hypothesis Test for Population Mean 11:04
- Stat 130 - Exam 1 Prep Video 1 23:20
- Stat 130 - Exam 1 Prep Video 2 23:30
- Stat 130 - Exam 1 Prep Video 3 18:41
- Stat 130 - Exam 1 Prep Video 4 07:24
- Stat 130 - Exam 2 Review - Module 8 17:48
- Stat 130 - Exam 2 Review - Module 9 15:51
- Stat 130 - Exam 2 Review - Module 10 15:28
- Multiplication Rule For Several Events - Example - Stress 03:51
- Multiplication Rule For Several Events - Example - BowTie 05:20
- Multiplication Rule For Several Events - Example - Gender 03:44
- Stat 130 - Exam 2 Review - Module 7 15:05
- Stat 130 - Exam 3 Review - Module 12 09:52
- Stat 130 - Exam 3 Review - Module 13 11:10
- Stat 130 - Exam 3 Review - Module 15 08:40
- Stat 130 - Exam 3 Review - Module 14 13:50
- Stat 130 - confidence intervals for means 13:11
- Stat 130 - Hypothesis Testing for Means Video 1 28:03
- Stat 130 - Hypothesis Testing for Means Video 2 06:03
- Stat 130 - Hypothesis Testing for Means Video 3 16:24
- Stat 130 - Hypothesis Testing for Means Video 4 04:41
- Stat 130 - Hypothesis Testing for Means Video 5 21:16
- At Least One Defect 16:11
- Create a Stem Leaf Plot and Comment on the Shape of the Distribution 11:06
Take this course with you
Download the app to continue lessons from your phone anytime.
