Statistics

Question 1

What is the mean?

Answer 1

Add all the values together and divide by the number of values.

Question 2

What is the median?

Answer 2

The middle value (Average middle 2 if odd number of values)

Question 3

What is the mode?

Answer 3

The most frequently observed value

Question 4

What is the standard deviation?

Answer 4

Estimate of the average variability (spread) of the data

Question 5

What is the 95% confidence interval?

Answer 5

The range of values around that statistics (so 95% of values will fit into between the range of values)

Question 6

What is standard error?

Answer 6

The standard deviation of the sampling distribution of a given statistic.

Question 7

What is the range?

Answer 7

The range in values (Maximum and minimum)

Question 8

What are the basic statistics?

Answer 8

The mean, mode, range, median, 95% confidence interval and standard deviatio.

Question 9

How do you find the basic statistics using SPSS?

Answer 9

1) Enter data into SPSS
2) Analyse
3) Descriptive statistics
4) Explore
5) Add the variable into the dependant list
6) OK

YOU MUST HAVE ALL DATA IN SEPARATE COLUMNS (i.e. do not stack)

Question 10

What is P?

Answer 10

The p value is the probability of falsely rejecting the null hypothesis

Question 11

What is the null hypothesis?

Answer 11

The null hypothesis is that there is no difference

Question 12

Why do we use statistics?

Answer 12

To test our data against the null hypothesis

Question 13

What does p < 0.05 mean

Answer 13

p < 0.05 is described as significant.

Essentially if its less than 0.05 you are 99.95% sure there is a significant difference!

Question 14

Example of hypothesis and null hypothesis?

Answer 14

Hypothesis: Paracetamol will reduce symptoms of a headache

Null hypothesis: Paracetamol may reduce symptoms of a headache

Question 15

What is normal distribution?

Answer 15

Normal distribution is:

• Ensures that the data is representative of a “normal population”
• Important for quantitative data
• Helps determine how we present data
• Helps determine what statistical test we use to analyse data

Question 16

What are the tests used for normal distribution?

Answer 16

To see whether data is normally distributed use;

• Kolmogorov - Smirnov test

OR

• Shapiro - Wilk test

Question 17

When do you use parametric or non parametric test?

Answer 17

P value is < 0.05 = NOT normally distributed = non parametric test

P value is > 0.05 = normally distributed = parametric test

Question 18

How can you test for normality i.e a Kolmogorov Smirnov test or Shapiro Wilko test?

Answer 18

You can do this at the same time as basic statistics in SPSS. YOU MUST HAVE ALL DATA IN SEPERATE COLUMNS (i.e. do not stack)

1) Enter data into SPSS
2) Analyse
3) Descriptive Statistics
4) Explore - Add the variable into the dependant list
5) Click plots
6) Click normality plot with tests
7) Histograms
8) Continue

Question 19

What would happen if one was significant and the other wasn’t?

Answer 19

It is not normally distributed they both need to be normally distributed in order to use the parametric test.

Question 20

What is a type 1 error?

Answer 20

Occurs when we believe that there is a genuine effect in our population, when in fact there isn’t

Question 21

What is a type 2 error?

Answer 21

Occurs when we believe there is no effect in the population, when in reality there is.

Question 22

What is one tailed?

Answer 22

A test of directional hypothesis i.e. x will predict y or x is different from y

Question 23

What is two tailed?

Answer 23

A test of non directional hypothesis i.e. x may or may not predict y or x is maybe different from y

Question 24

What do we do with parametric data?

Answer 24

• Use when data is normally distributed

When comparing 2 groups:

• Independent T test - two different experimental conditions/ groups
• Dependant T test - two groups that are dependant on each other

Comparing 3 or more groups:

One way ANOVA - You have 3 or more groups

Question 25

How can you determine if your data is dependant or independent?

Answer 25

Independent = Compare participants in different group E.G. Different people receiving different treatments. Dependant = Compare participants in the same group E.G. Same people tested twice receiving the same treatment

Question 26

What to do with 2 groups and data that is normally distributed?

Answer 26

2 groups and data that is normally distributed Dependant on each other OR Independent groups Dependant T test Independent T test

Question 27

How do you do a dependant T test?

Answer 27

1) Analyse 2) Compare means 3) Paired samples t test Then add the data from test 1 under variable 1 and data for test 2 under variable 2 then press ok

Question 28

How do you do independent T test?

Answer 28

Stack variables in one column. Then add group numbers (e.g. 1 and 2) into the next column and define groups 1) Analyse 2) compare means 3) Independant samples T test Then add the column of stacked data into the test variable box and the groups column into the grouping variable box. Define groups and press ok Also check levene's test, are equal variances assumed?

Question 29

What does sig .000 mean?

Answer 29

P value < 0.0001

Question 30

What is levene's test?

Answer 30

Tests whether groups are similar

Question 31

What does ANOVA tell us?

Answer 31

ANOVA (Analysis of variance) which tell us if there is a difference between all groups But an ANOVA DOES NOT tell us where the difference is between groups, e.g. is group A different from group B and C or just group B We use Post - hoc tests to compare each group to work out which is different from each other

Question 32

What do we for more then 3 groups?

Answer 32

If 3+ groups and data is normally distributed? Enter data into SPSS - Analyse - compare means - One Way ANOVA - Select your post hoc test (LSD and Tamhane's) - click options - choose homogeneity of variance test Check ANOVA sig/ P value is it < 0.05 Yes | No Check homogeneity of variance test is that significant? | Just report ANOVA, no need for further analysis No = Use LSD Post Hoc results Yes = Use Tamhane Post Hoc results MUST GROUP DATA E.G. ADD VARIABLE 1 TO TEST VARIABLE BOX AND GROUPS/VARIABLE 2 INTO GROUPING VARIABLE BOX. CHECK DESCRIPTIVES TO GET BASIC STATS TOO

Question 33

How does ANOVA work?

Answer 33

ANOVA is < 0.05, check homogeneity of variance test We use LSD post hoc as homogeneity of variance test > 0.05 if (<0.05 use tamhanes)

Question 34

What is ANCOVA

Answer 34

Compares several means but adjusts for the effects of one or more other variables

Question 35

What is repeated measures ANOVA

Answer 35

ANOVA conducted when any independent variable or variables have been measured from the same participants in all conditions

Question 36

What is factorial ANOVA?

Answer 36

2 or more independent variables or predictors

Question 37

Tell me about non - parametric data?

Answer 37

- Use when data is NOT normally distributed Comparing 2 groups: Mann Whitney test - 2 different experimental conditions/groups, a non - parametric version of an independent test Wilcoxon Signed rank test - 2 groups that are dependent on each other, a non parametric version of a dependent t test. Comparing 3 or more groups: - Kruskal Wallis Test - You have three or more groups , a non - parametric version of a One - way ANOVA

Question 38

How to do a Wilcoxon signed rank t test?

Answer 38

1) Analyse 2) non parametric tests 3) related samples Under fields tab transfer your parameters to the test field box Go to settings and choose Wilcoxon matched pair signed rank test (2 samples)" Press run

Question 39

How to do a Mann Whitney T test?

Answer 39

Stack variables in one column. Then add group numbers into the next column e.g. 1 and 2. They define groups 1) Analyse 2) Non parametric test 3) Independent samples 4) Automatically compare distribution across groups. Then add the column of stacked data into the Test Variable box and the groups column into the grouping variable box Settings - Customize tests - Select Mann Whitney U (2 samples) - Run

Question 40

How to do a Kruskal Wallis test?

Answer 40

3 + groups and data is NOT normally distributed 1) Enter data into SPSS 2) Rearrange data like you would for One - way ANOVA 3) Analyse 4) Non parametric test 5) Independent samples 6) Automatically compare distributions across groups 7) Add BMD/variable 1 into test variable box and groups/variable 2 into groups box Go to settings customize tests and Kruskal Wallis and run Check sig p value, is it <0.05 If yes, Run multiple Mann Whitney tests between each group and report the p values and determine which group shows significance If no, just report the p value no need for further analysis.

Question 41

How to run a post hoc analysis?

Answer 41

To run a post hoc analysis (a bit like we did with a one way ANOVA) we need to run a individual Mann Whittney Tests which is a bit time consuming N.B. To do this you only need to run 2 groups at a time it will not work otherwise

Question 42

What is correlation?

Answer 42

Correlation is measuring the relationship between 2 variables. Positive = one increases the other increases Negative - As one increases the other decreases. There are 2 types of tests: For parametric data = Pearson's correlation coefficient For non parametric data = Spearman's correlation coefficient

Question 43

What is correlation coefficient score?

Answer 43

A correlation coefficient score has to lie between + 1 and - 1 A + 1 = perfect positive a -1 = perfect negative 0 = no relationship

Question 44

Correlation grading

Answer 44

0.0 - 0.3 = Poor correlation 0.3 - 0.5 = Low correlation 0.5 - 0.7 = Moderate correlation 0.7 - 0.9 = Strong correlation 0.9 - 1 = Very strong correlation can refer to both positive and negative

Question 45

How to do pearson?

Answer 45

Is your data normally distributed Yes = pearson Parametric data = normally distributed Enter data next to each other Analyse - correlate - bivariate - tick pearson for parametric data

Question 46

How to do spearmans?

Answer 46

Is your data normally distributed No = Spearman Non - parametric - not normally distributed Enter data next to each other Analyse - correlate - Bivariate - Tick spearman for non parametric data

Question 47

How do you report the correlation?

Answer 47

You should report the Pearson correlation coefficient as r and the p value For example: r = 0.796 (p<0.001) indicates a strong positive correlation You should report the spearman correlation coefficient as p and the p value For example: p = 0.796 (p<0.001) indicates a strong correlation

Question 48

What is regression?

Answer 48

Simple regression = Predict an outcome variable from one predictor variable Multiple regression = Predict an outcome from several types of predictor variables Binary logistic regression = Predict a categorial outcome from several types of predictor variables.

Question 49

Simple regression?

Answer 49

Dependent = what you are trying to predict Independent = What you are using to try and predict the variable Add data into SPSS next to each other - Analyse - Regression - Linear R = your Pearson's correlation R square = Look a it telling you how much one variable accounts for the other e.g. 0.948 = 94.8% Sig level = <0.001 = does significantly predict Multiple regression = aim for n = 5 - 10 people It tells us which variable predict the outcome

Question 50

What is nominal data?

Answer 50

Nominal ( Categories wiht no obvious order) : Gender, smoker or non - smoker, eye colour

Question 51

What is ordinal data?

Answer 51

Ordinal (Categories that can be ranked in order) : Shoe size, Age categories

Question 52

Why do we use Pearson's chi squared test?

Answer 52

To look at the relationship between two categorical variables Chi squared will test the null hypothesis, i.e. that they are similar