+ - 0:00:00
Notes for current slide
Notes for next slide

Exam Revision

Lecture 11

Drs Jennifer Mankin and Milan Valášek

30 April 2021

1 / 25

Today

  • Exam Details

    • Types of Questions

  • Concepts to Revise

    • Kahoot! Revision Practice

  • Tips for Success

  • Revision Resources

2 / 25

Exam Details

  • Multiple choice exam online via Canvas

    • Weighted 50% of your overall module mark

  • 120 minutes (two hours) + 30 minutes for technical problems

    • Must attempt the exam in the 24-hour period it is available

    • If you have any adjustments, these will be applied automatically

    • If something comes up unexpectedly, apply for exceptional circumstances

3 / 25

Exam Details

  • Multiple choice exam online via Canvas

    • Weighted 50% of your overall module mark

  • 120 minutes (two hours) + 30 minutes for technical problems

    • Must attempt the exam in the 24-hour period it is available

    • If you have any adjustments, these will be applied automatically

    • If something comes up unexpectedly, apply for exceptional circumstances

  • Questions cover all lectures and tutorials

    • Includes reading and interpreting R output!

    • You will NOT need to use R yourself to complete the exam

3 / 25

Types of Questions

  • Definitions and concepts

  • Reading R output for analyses, figures, and tables

  • Some calculations (no more than basic maths)

4 / 25

Concepts to Revise

Part one: Foundations of Statistics

5 / 25

Week 1

Lecture

  • Distributions

  • The normal and standard normal distributions

  • Samples and estimates

  • The sampling distribution and standard error

  • The Central Limit Theorem

Tutorial

  • Reading tibbles of data

  • Using the pipe %>%

6 / 25

Week 2

Lecture

  • Point and interval estimates

  • Confidence intervals

  • The t-distribution

Tutorial

  • Critical values

  • Cut-off points

7 / 25

Week 3

Lecture

  • Types of hypotheses

  • Logic and procedure of null hypothesis significance testing (NHST)

  • Using and interpreting p-values

Tutorial

  • Types of hypotheses

  • Logic and procedure of null hypothesis significance testing (NHST)

  • Using and interpreting p-values

8 / 25

It's Kahoot! Time

9 / 25

Concepts to Revise

Part two: Statistical Testing

10 / 25

Week 4

Lecture

  • Understanding the value of r and its relationship to causation

  • Reading a correlation matrix and scatterplot

  • Interpreting and reporting significance tests of r

Tutorial

  • Reading and interpreting the output of cor() and cor.test()

  • Reporting the results of a correlation analysis in APA style

11 / 25

Week 5

Lecture

  • Concepts behind goodness-of-fit and association

  • Reading tables and figures of counts

  • Interpreting and reporting significance tests of χ2

Tutorial

  • Reading and interpreting the output of chisq.test() and tables of expected and observed counts

  • Reporting the results of a χ2 analysis in APA style

12 / 25

Week 6

Lecture

  • Concepts behind comparing two means

  • Independent and paired-samples t-tests

  • Where the t-statistic comes from and what it means

  • How to read histograms and means plots

Tutorial

  • Reading and interpreting a means plot

  • Reading and interpreting the output of t.test()

  • Reporting the results of a t-test in APA style

13 / 25

It's Kahoot! Time

14 / 25

Concepts to Revise

Part three: Stats Wars (the Linear Model)

15 / 25

Week 7

Lecture

  • Concepts behind statistical modeling

  • The equation for a linear model with one predictor

  • How to interpret b-values in the linear model equation

  • Using the equation to predict an outcome for given values of the predictors

  • How to read scatterplots and lines of best fit

Tutorial

  • Understanding the meaning of b0

  • Using the lm() function to create a linear model

  • Interpreting the output from lm() and translating it into the linear model equation

16 / 25

Week 8

Lecture

  • How to interpret b-values in the linear model equation

  • Confidence intervals and p-values for b estimates

  • Interpreting R2

Tutorial

  • Deviations and residuals

  • Using the lm() function to create a linear model

  • Interpreting the output of summary(), broom::tidy(), and broom::glance()

17 / 25

Week 9

Lecture

  • Adding predictors to the linear model

  • Interpreting b-values for multiple predictors

  • Comparing b-values with standardised Bs

  • Transforming variables in the model

Tutorial

  • Using the lm() function to create a linear model with multiple predictors

  • Interpreting the output of summary(), broom::tidy(), and broom::glance()

  • Interpreting the output of QuantPsyc::lm.beta()

18 / 25

Week 10

Lecture

  • Categorical predictors in the linear model

  • Comparing models with F

  • Interpreting R2 and adjusted R2 for models with multiple predictors

Tutorial

  • Using the lm() function to create a linear model

  • Interpreting the output of anova() for model comparison

19 / 25

It's Kahoot! Time

20 / 25

Tips and Tricks

21 / 25

Tips for Revision

  • Work through practicals again

    • Do the tasks, don't just read the answers!

  • Look through quiz answers

22 / 25

Tips for Revision

  • Work through practicals again

    • Do the tasks, don't just read the answers!

  • Look through quiz answers

  • Watch/read other resources

    • e.g. Khan Academy, YouTube

  • Ask questions on Piazza

22 / 25

Tips for Preparation

  • Memorise key concepts and definitions

    • e.g. the p-value, standard error

  • Put together a glossary of terms

    • Build it collaboratively if you like!

  • Learn to ballpark numbers

  • Know how to navigate the output for statistical tests

Lots of detail and more advice in last week's StatsChats!

23 / 25

Resources

  • Sample exam: Half the length, all the fun

    • Take as many times as you like on Quizzes!

    • Same kind of questions as the real exam

  • Handout for this lecture

    • Use as a revision guide

  • Everything from PAAS and AnD!

24 / 25

Have a fantastic summer!!!

25 / 25

Today

  • Exam Details

    • Types of Questions

  • Concepts to Revise

    • Kahoot! Revision Practice

  • Tips for Success

  • Revision Resources

2 / 25
Paused

Help

Keyboard shortcuts

↑, ←, Pg Up, k Go to previous slide
↓, →, Pg Dn, Space, j Go to next slide
Home Go to first slide
End Go to last slide
Number + Return Go to specific slide
b / m / f Toggle blackout / mirrored / fullscreen mode
c Clone slideshow
p Toggle presenter mode
t Restart the presentation timer
?, h Toggle this help
Esc Back to slideshow