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Seminar 3 (2011)

Seminar 3 (2011). Exploring Assumptions, T-test analysis and writing up your lab report. Plan for today. Why is .05 so important Why are Degrees of freedom different on the within and between t-tests What do we need to do before computing a t-test

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Seminar 3 (2011)

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  1. Seminar 3 (2011) Exploring Assumptions, T-test analysis and writing up your lab report.

  2. Plan for today • Why is .05 so important • Why are Degrees of freedom different on the within and between t-tests • What do we need to do before computing a t-test • Plot the variables using a histogram (visual check for normality) • Check for skewdness • Check for kurtosis • Running a T-test • Writing up the lab report.

  3. Designing an experiment • Hypothesis • When you are designing an experiment you have two types of hypothesis • Experimental (Exciting) hypothesis • You predicted what the result will be • Null (Dull) hypothesis • The findings are just down to chance • Variables • The variable you change (Independent) • The result of that change (Dependent)

  4. ShandyStudy • My friend claimed that he can tell the difference between 2 pints of Shandydepending on how it was made • Where the lager went in first Vs. • Where the lemonade went in first

  5. ShandyStudy • Hypothesis • My Friend CAN taste the difference between pints where lemonade has gone in first compared to where the lager has gone in first. • The answers are down to chance • Variables • Independent Variable: Which order the 2 ingredients go in. • Dependent Variable: His answer

  6. Lets do the Study • Lets have drinks some with lager first (LF) and some with lemonade in first (LemF). • There will be an equal number of LF and LemF drinks. • But you will not know which order they were in. • If I gave 2 drinks, there are only 2 orders the pints can be placed: LF LemForLemFLF • With only 2 possible orders the participant has a 50% chance of getting the right answer. • Which is not very convincing, as I hate Shandy and I would also have a good chance of getting the answer right just by guessing

  7. So lets make things more complicated by having 6 drinks • There are 20 orders in which the pints can be placed. • If your guessing she would have a 1 in 20 chance of getting the correct answer. • 1 ÷ 20=.05 to make that in to a percentage 5% chance of guessing correctly • Lets say the participant did get the answer right six times in a row. • I would be pretty convinced. And so would Fisher LemFLemFLemFLF LFLF

  8. Who is Fisher? • Fisher (1925) suggested that only when we are 95% certain that a result is genuine (not happening by chance) we should accept it as being true. • This is the basic principle of saying that something is statistically significant. • It may not really be true (you may have just guessed) but this is where the agreed line has been drawn.

  9. So Back to the hypotheses • Hypothesis • Experimental (Exciting) hypothesis: You can taste the difference between pints that have the ingredients going in a different order. • Null (Dull) hypothesis: She is just guessing, answers are just down to chance. • You have not “proven” either of the hypotheses. • But we can say the Null one is unlikely or reject it ; we are 95% sure it is not true

  10. Can we ever “prove” the experimental hypothesis ? • Well No, • It is like the lottery, the odds of picking the 6 correct numbers is 1 in 13,983,815. • So we can be very sure we will not pick the correct numbers, it is significantly unlikely. • But then again someone does manage to do this nearly every week. • Which is why we can only say the Null hypothesis is statically unlikely to be true.

  11. Degrees of freedom • Paired Samples t-test or Within-subjects -subjects t-test • Our IV: Recall condition • Level 1 : Individual recall • Level 2 : Group recall

  12. Degrees of freedom • Independent Samples t-test or Between-subjects t-test • Our IV: Group size • Level 1 : 2 person group • Level 2 :5 person group • 5 person • group • 2 person • group

  13. Festival Hygiene • Field (2009) looked at the hygiene levels of Download festival attendees across the 3 days. • Today we are going to be looking at the hygiene levels of Sonispherefestival attendees across the 2 day festival.

  14. Festival Hygiene • Field (2009, p.94) reports a scale ranging between: 0 = “You smell like a corpse that’s been left to rot up a skunk’s arse” 4 = “You smell of sweet roses on a fresh spring day” Our survey of Sonisphere festival used the same scale

  15. Open the Data file • The data set we are using is called “Sonisphere Festival” • It is on the U drive • U24103 • Seminar 3

  16. Use the EXPLORE function to produce skew and kurtosis statistics • Skew should = 0 in perfect normally distributed data. Skew = 0 (normal) Negative Skew Positive Skew = +

  17. Use the EXPLORE function to produce skew and kurtosis statistics • Kurtosis should = 0 in perfect normally distributed data. • ve kurtosis • “platykurtosis” + ve kurtosis “leptokurtosis” Kurtosis = 0 “mesokurtosis”

  18. What’s an acceptable level of skew and kurtosis for a t-test? Rules of thumb- - Skewness ok if less than 0.8 - Kurtosis ok if between -2 & +2 Are our levels of skew and kurtosis acceptable?

  19. Our sample includes people with both standard and VIP tickets. • Use Select Cases if and exclude all the people with VIP tickets • Now create the Histograms and Descriptives again. • Then Answer Questions 1 to 6. • Take Select Case if Off

  20. ******Take off the filter and Select all cases ***** We want to see if there is a significant difference in hygiene levels of people with Standard and VIP tickets. What kind of t-test do we need to use for our hypothesis? • Independent (Between-subjects t-test ) • Paired-samples (Within-subjects t-test

  21. Recode in to different variable • Transform • Recode in to differentvariable • Move Tick_Type across • Name Two_Tick_Type • Change • Old and New Values • 0->0, 1->1, 2->1, 3->1, 4->1 • Continue then OK

  22. How to do an independent-samples t-test using SPSS An independent-samples t-test involves comparing two different groups on a single dependent variable. Between-subjects t-test

  23. For the IV SPSS needs to be told what the label numbers are of the two groups we want to compare Dependent variable (DV) goes here Independent variable (IV) goes here

  24. If the significance for Levene's test is: greater-than (>) .05 use the top row “Equal variables assumed”. .05 or below (=<), then use the bottom row "Equal Variances not Assumed" . Means and Std. Deviations of the two groups on the DV Are two rows for the t-test result. Only one row, defined by the result of the Levene’s test, is looked at

  25. If the significance for Levene's test is 0.05 or below, then use the bottom row "Equal Variances not Assumed" test. Otherwise use the top row “Equal variables assumed”. Levene's test is greater than .05 therefore we need to use the top row. t=2.49 df=98 p=.015 There was a significant effect of perceived group size, t(98)=2.49 p=.015. Participants recall a grater number of items when they thought they were in a group of two (M=5.66, SD= 1.44) as apposed to a group of 5 people (M=4.92, SD=1.53)

  26. If the significance for Levene's test is 0.05 or below, then use the bottom row "Equal Variances not Assumed" test. Otherwise use the top row “Equal variables assumed”. Levene's test is less than .05 therefore we need to use the bottom row. t=2.49 df=97.56 p=.015 There was a significant effect of perceived group size, t(97.56)=2.49 p=.015. Participants recall a grater number of items when they thought they were in a group of two (M=5.66, SD= 1.44) as apposed to a group of 5 people (M=4.92, SD=1.53)

  27. How to do a paired-samples t-test using SPSS A paired samples t-test would allow us to compare the same participants performance on 2 variables Within-subjects t-test

  28. Mean for individual scores Mean for group scores

  29. Means (and SDs) for the two variables Note: we ignore minus signs when reporting t values p <.001 t = 19.71 df=49 p=.0000000000000000000000000000000000004738209580081584 Standard deviation of the difference between the two variables Mean difference between the two variables

  30. t=19.71 df=99 p<.001 There was a significant effect of perceived group, t(99)=19.71 p<.001. Participants recall a grater number of items when they thought they were working on there own (M=8.93, SD= 1.18) as apposed to a group (M=5.29, SD=1.53)

  31. We are going to stop for 20 min so you can work through questions 1- 8 on the worksheet and have a break. **Question 7 is answered using the day one data** Field Easter Egg hunt The are 9 hidden messages (Easter eggs) In the Core TextField (2009). The first person to show me or john a Easter egg will receive a Easter egg*. *One per person. Field, A. (2009) Discovering Statistics Using SPSS (third edition). Sage publications: London, UK.

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