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Inferential statistics allows us to draw conclusions from data that might not be immediately obvious. This course focuses on enhancing your ability to develop hypotheses and use common tests such as ANOVA tests, and regression to validate your claims. This course will cover estimating parameters of a population using sample statistics, hypothesis testing and confidence intervals, t-tests and ANOVA, correlation and regression and chi-squared test.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

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Course Credit: San Jose State University

Course Curriculum

Module-1
Lauren’s Intro Video 00:01:00
Intro 00:01:00
Klout 00:02:00
Klout Parameters 00:01:00
Klout Sampling Distribution (Mean) 00:01:00
Klout Sampling Distribution (SD) 00:03:00
Klout 00:01:00
What Do You Get with a Good Klout Score? 00:02:00
Location of Mean on Distribution 00:01:00
Probability of Obtaining Mean 00:01:00
Module-2
Does Low Probability = Causation? 00:01:00
Increase Sample Size 00:01:00
Location of Mean 00:01:00
Probability of Mean 00:01:00
Something Fun 00:02:00
Summary 00:02:00
Mean of Treated Population 00:01:00
Population Mean vs. Sample Mean 00:01:00
Percent of Sample Means 00:01:00
Approximate Margin of Error 00:01:00
Module-3
Interval Estimate for Population Mean 00:03:00
Confidence Interval Bounds 00:01:00
Exact Z-Scores 00:01:00
Sampling Distributions 00:01:00
95% CI with Exact Z-Scores 00:01:00
Generalize Point Estimate 00:01:00
Generalize CI 00:01:00
CI Range for Larger Sample Size 00:01:00
CI When n = 250 00:01:00
Bigger Sample, Smaller CI 00:01:00
Module-4
Z for 98% CI 00:01:00
Find 98% CI 00:01:00
Critical Values of Z 00:01:00
Engagement Ratio 00:01:00
Hypothesis Testing Song 00:01:00
Point Estimate Engagement Ratio 00:01:00
Standard Error 00:01:00
CI Bounds 00:01:00
Generalize CI 00:01:00
Margin of Error 00:01:00
Module-5
Rate Engagement and Learning 00:01:00
Results from Sample 00:01:00
What Statistics? 00:01:00
Sampling Distributions 00:01:00
Z-Scores of Sample Means 00:01:00
Probability Sample Mean Is at Least… 00:01:00
What Does This Mean? 00:01:00
Wrap-Up 00:01:00
Likely or Unlikely 00:01:00
Alpha Levels 00:01:00
Module-6
Z-Critical Value 0.05 00:01:00
Critical Values 0.01 00:01:00
Critical Values 0.001 00:01:00
Critical Regions 00:02:00
Significance 00:01:00
Darts 00:01:00
Z-Score 007 00:01:00
Two-Tailed Critical Values 0.05 00:01:00
Two-Tailed Test 00:01:00
Two-Tailed Probability 00:01:00
Two-Tailed Critical Values 0.01 00:01:00
Two-Tailed Critical Values 0.001 00:01:00
Module-7
Hypotheses 007 00:03:00
Fail to Reject the Null 00:01:00
Evidence to Reject the Null 00:01:00
Mean and SD 00:02:00
Null Hypothesis 00:01:00
Alternative Hypothesis 00:01:00
One tailed or two tailed 00:02:00
Conduct Hypothesis Test 00:01:00
Critical Values 0.05 00:01:00
Z-Score of Sample Mean 00:01:00
Module-8
Results of Hypothesis Test 00:01:00
Increase Sample Size 00:01:00
Reject or Fail to Reject 00:01:00
Probability of Obtaining Mean 00:01:00
Decision Errors 00:01:00
Hot Beverage 00:01:00
Raining 00:01:00
What Happened? 00:01:00
What Happened? 00:01:00
Prone to Misinterpretations 00:01:00
To Finish This Lesson 00:01:00
Module-9
Hypothesis Testing 00:01:00
Increase Engagement? 00:01:00
t-Distribution 00:02:00
Guinness 00:01:00
Degrees of Freedom 007 00:01:00
DF – Choose n Numbers 00:01:00
DF – Add to 10 00:01:00
DF – Marginal Totals 00:01:00
DF – Sample SD 00:02:00
Module10
t-Table 00:02:00
One-Tailed t-Test 00:01:00
Two-Tailed t-Test 00:01:00
Bounds of Area 00:01:00
Affect t-Statistic 00:01:00
One-Sample t-Test 00:02:00
Increase t 00:01:00
Finches 00:02:00
Finches – n and DF 00:01:00
Finches – Mean and s 00:01:00
Finches – Find t-Statistic 00:01:00
Finches – Decision 00:01:00
Module-11
P-Value 00:01:00
Visualize P-Value 00:01:00
Find P-Value 00:01:00
Rent – t-Critical Values 00:01:00
Rent – t-Statistic 00:01:00
Rent – Decision 00:01:00
Rent – Cohen’s d 00:01:00
Rent – CI 00:01:00
Rent – Find CI 00:01:00
Rent – Margin of Error 00:01:00
Rent – Increase n 00:01:00
Module-12
Independent Samples 00:04:00
Keyboards 007 00:01:00
Keyboards: Point Estimate for Difference 00:01:00
Keyboards – SD of Differences 00:01:00
Keyboards – t-Statistic 00:01:00
Keyboards – t-Critical Values 00:01:00
Keyboards – Decision 00:01:00
Keyboards – Cohen’s d 00:01:00
Keyboards – CI for Dependent Samples 00:01:00
Module-13
Notation for Difference 00:01:00
Types of Designs 00:02:00
Effect Size 00:01:00
Everyday Meaning 00:01:00
Types of Effect-Size Measures 00:01:00
Statistical Significance 00:02:00
Cohen’s d 00:01:00
r^2 00:01:00
Compute r^2 00:01:00
Module-14
Report Results 00:03:00
Report CI Results 00:01:00
Report CI Results 2 00:01:00
Report Results Effect Size 00:01:00
One-Sample t-Test 00:01:00
Mu 00:01:00
Dependent Variable 00:01:00
Treatment 00:01:00
Null Hypothesis 00:01:00
Alternative Hypothesis 00:01:00
Hypotheses 00:01:00
Module-15
Which-Tailed Test? 00:01:00
Degrees of Freedom 00:01:00
t-Critical 00:01:00
SEM 00:01:00
Mean Difference 00:01:00
t-Statistic 71 00:01:00
Critical Region 00:01:00
P-Value 00:01:00
Statistically Significant 00:01:00
Meaningful Results 00:01:00
Module-16
Cohen’s d 00:01:00
r^2 00:01:00
Margin of Error 00:01:00
Compute CI 00:01:00
Independent Samples 00:04:00
Standard Error 00:04:00
Meal Prices 00:01:00
Average Meal Price 00:01:00
SD for Meal Price 00:01:00
Meal Price SEM 00:01:00
Meal Price t-Statistic 00:01:00
Calculate t-Statistic 00:01:00
Module-17
t-Critical Values 00:01:00
Gettysburg or Wilma? 00:01:00
Acne Medication 71 00:01:00
Acne Medication t-Statistic 00:01:00
Acne Medication – t-Critical Values 00:01:00
Acne Medication – Decision 00:01:00
Who Has More Shoes? 00:01:00
Mean Number of Shoes 00:01:00
Shoes – Standard Error 00:01:00
Shoes – t-Statistic 00:01:00
Shoes – Decision 00:01:00
Shoes – 95% CI 00:01:00
Shoes – Calculate CI 00:01:00
Gender and Shoes 00:01:00
Module-18
Pooled Variance Sum of Squares 00:02:00
Calculate Pooled Variance 00:01:00
Corrected Standard Error 00:01:00
t-Statistic 00:01:00
t-Critical and Decision 00:01:00
Assumptions 00:02:00
Intuition 00:01:00
Number of t-Tests 00:01:00
Extended t-Test Numerator 00:01:00
Grand Mean 00:01:00
Module-19
Between-Group Variability 00:01:00
Significantly Different Means 00:01:00
Sample Variability and Significance 00:01:00
ANOVA 00:01:00
Hypotheses 00:01:00
Within-Group Variability 00:01:00
Between-Group Variability 00:01:00
F-Ratio 00:01:00
Visualize Statistical Outcome 00:01:00
Formalize Within-Group Variability 00:02:00
Module-20
Formula for F-Ratio 00:01:00
Degrees of Freedom 00:01:00
Total Variation 00:01:00
F-Distribution 00:01:00
F-Distribution Shape 00:02:00
Table for F-Critical 00:01:00
Sample Means and Grand Mean 00:01:00
SS Between 71 00:01:00
SS Within 00:01:00
Module-21
Degrees of Freedom 00:01:00
Mean Squares 00:01:00
F-Statistic 00:01:00
F-Critical 00:01:00
Decision 00:01:00
Cows and Food 00:01:00
Grand Mean 1111 00:01:00
Group Means 00:01:00
SS Between 00:01:00
SS Within 00:01:00
Module-22
Degrees of Freedom 00:01:00
Mean Squares 00:01:00
F-Statistic 00:01:00
F-Critical and Decision 00:01:00
Deviation from Grand Mean 00:01:00
SS Total 00:01:00
Conclusion 00:01:00
Module-23
Multiple Comparison Tests 00:03:00
Tukey’s HSD 00:01:00
Which Differences Are Significant? 00:01:00
Cohen’s d for Multiple Comparisons 00:01:00
η^2 00:01:00
Range of η^2 00:01:00
Software Output 00:02:00
Missing Mean Differences 00:01:00
Different Sample Sizes 00:01:00
Grand Mean 00:01:00
SS Within 00:01:00
Module-24
Degrees of Freedom 00:01:00
MS and F 00:01:00
Proportion Due to Drug Type 00:01:00
Power 007 00:01:00
ANOVA Assumptions and Wrap-Up 00:03:00
Relationships 00:01:00
The Variables x and y 00:01:00
Show Relationship 00:01:00
Scatterplot 00:01:00
Stronger Relationship 00:01:00
Module-25
As x Increases 00:01:00
Strength and Direction 00:01:00
Correlation Coefficient 00:02:00
Match with r 00:01:00
Age in Months and Years 00:01:00
Hours Asleep vs. Awake 00:01:00
Create Scatterplot 00:01:00
Calculate r 00:01:00
Stronger 00:01:00
Hypothesis Testing for ρ 00:01:00
Module-26
Testing for Significance 00:01:00
CI for ρ 00:01:00
Find p 00:01:00
Add Outlier 00:01:00
Correlation vs. Causation 00:02:00
Fallacies 00:03:00
Intro to Linear Regression 00:01:00
Airplane Flights 00:02:00
Symbolize Regression Equation 00:02:00
Guess Best Fit Line 00:01:00
Module-27
Minimize Sum of Squares 00:02:00
Calculate r 007 00:01:00
Calculate Standard Deviations 00:01:00
Calculate Slope 00:01:00
Find y-Intercept 00:01:00
What Point Does the Line Go Through? 00:01:00
Calculate Means 00:01:00
Calculate y-Intercept 00:01:00
Travel 4000 Miles 00:01:00
Additional Cost per Mile 00:01:00
Module-28
Cost to Travel 0 Miles 00:01:00
Travel on a Budget 00:01:00
Which Has More Error? 00:01:00
Standard Error of Estimate 00:01:00
Confidence Intervals 00:02:00
Hypothesis Testing for Slope 00:01:00
t-Test for Slope 00:01:00
R Output 00:02:00
Factors Affecting Linear Regression 00:01:00
Summary of Linear Regression 00:02:00
Intro to Multiple Regression 00:03:00
Module-29
Alcohol, Religiosity, & Self-Esteem 00:01:00
Make Predictions 00:01:00
Relationship 00:01:00
Causation 00:01:00
Module-30
Applets 00:01:00
Scales of Measurement 007 00:02:00
Choose Type of Data 00:01:00
Non-Parametric Tests 00:01:00
Mount Shasta 00:01:00
Expected Frequencies 00:01:00
Observed Frequency 00:01:00
Hypotheses Percent 00:01:00
Hypotheses Frequency 00:01:00
Expected Frequencies 00:01:00
Module-31
χ^2 Goodness-of-Fit Test 00:02:00
χ^2 Statistic 00:01:00
Observed Equals Expected 00:01:00
χ^2 Values 00:01:00
Degrees of Freedom 00:01:00
Which Has More df? 00:01:00
Calculate χ^2 Statistic 00:01:00
Find df 00:01:00
Calculate p 00:01:00
χ^2 Test for Independence 00:01:00
Module-32
Remember Details 00:01:00
Broken Glass 00:01:00
Expected Frequencies 00:01:00
Calculate χ^2 Statistic 00:01:00
Degrees of Freedom 00:01:00
Decision 00:01:00
Module-33
Effect Size 00:01:00
Calculate Cramér’s V 00:01:00
Assumptions and Restrictions 00:01:00
Summary 00:02:00
Congrats 00:01:00
Lauren’s Outro Video 00:01:00
Tutorial 00:08:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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