Certificate in Inferential Statistics (Udacity) - Edukite

10/10/2019

Certificate in Inferential Statistics (Udacity) - Edukite

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Certi cate in Inferential Statistics (Udacity) ( 9 REVIEWS ) 

490 STUDENTS

Inferential statistics allows us to draw conclusions from data that might not be immediately obvious.

This course focuses on enhancing …

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1 YEAR LEVEL 2 - CERTIFICATE COURSE BADGE COURSE CERTIFICATE

327

NUMBER OF UNITS NUMBER OF QUIZZES

0

6 HOURS, 27 MINUTES

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CURRICULUM

REVIEWS

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 con dence 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 Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certi cate at a cost of £49.

Having an Of cial Edukite Certi cation is a great way to celebrate and share your success. You can: Add the certi cate to your CV or resume and brighten up your career Show it to prove your success Course Credit: San Jose State University https://edukite.org/course/certificate-in-inferential-statistics-udacity/

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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

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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



Con dence 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



00:01:00

Module-4



Z for 98% CI

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

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

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

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



Signi cance



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

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

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

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

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

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

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

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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 Signi cance



00:02:00

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

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

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

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 Signi cant



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

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

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

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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



Signi cantly Different Means



00:01:00



Sample Variability and Signi cance



00:01:00



ANOVA



00:01:00



Hypotheses



00:01:00



Within-Group Variability



00:01:00

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

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

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

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

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

Which Differences Are Signi cant?



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

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

Scatterplot



00:01:00



Stronger Relationship



00:01:00

Module-25



As x Increases



00:01:00



Strength and Direction



00:01:00



Correlation Coef cient



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 Signi cance



00:01:00



CI for ρ



00:01:00



Find p



00:01:00



Add Outlier



00:01:00

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

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

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

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



Con dence 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



00:01:00

Module-30



Applets

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

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

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

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

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

Submit Your Assignment



00:00:00



Certi cation



00:00:00

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