Research Methods 1&2

Question 1

What does the PPPAC Cycle of research stand for?

Answer 1

->Problem-> Plan -> Data -> Analysis -> Conclusion ->

Question 2

Why is the research question important in statistical analysis?

Answer 2

The research question drives the research - it is the reason for the research i.e it gives the research it’s purpose and context.

Question 3

What is the difference between descriptive and psychological interpretations?

Answer 3

Descriptive = describe relationships e.g men have higher self-esteem on average than women

Psychological = explanatory/drawing conclusions e.g why do men have higher self-esteem on average than women.

Question 4

What is a hypothesis?

What is the difference between a theoretical hypothesis and a research hypothesis?

Answer 4

Hypothesis = a plausible answer to a research question
Theoretical hypothesis = Regards causal links between constructs
Research hypothesis = regards specific statements about variables i.e expected observations.

Question 5

What are the four different measurement formats?

Answer 5

Nominal, Ordinal, Interval, Ratio

Question 6

Describe nominal measurement formats

Answer 6

Categorical (non-continuious), no ‘rank-order’ e.g gender: male or female

Question 7

Describe Ordinal measurement formats

Answer 7

Similar to nominal - both are categorical. However Ordinal categories are in rank order i.e some categories represent more of the variable than another. e.g, first to last place

The difference between the categories DOES NOT have to be equal

Question 8

Describe Interval and ratio measurement formats

Answer 8

Categories in rank order where the difference between categories are EQUAL.

e.g age in years (NOT under 18, 18-25, 26-39 <- this is ordinal)

Ratios differ from interval variables in that ratio variables have a true zero i.e a score of 0 indicates that a person has none of that property.

Question 9

What is a categorical variable?

Which two of the four measurement formats are categorical?

Answer 9

Variables where the different levels represent different categories but provide no information about the differences between levels (or categories). i.e not meaningful as a number. E.g religious affiliation or gender.

Nominal and Ordinal

Question 10

What is a continuous variable?

Which two of the four measurement formats are categorical?

Answer 10

Variables where the different levels of a variable have a definite order and the differences between levels are known to be equal. i.e meaningful as a number. (e.g counting up test results and age in years)

Interval and ratio

Question 11

What are ‘descriptive statistics’?

Answer 11

aka ‘summary statistics’ describe data in a simpler form, merely listing all the scores obtained on all of the variables.

Question 12

What are the three main types of descriptive statistics?

Answer 12

Univariate, bivariate, multivariate

Question 13

What are univariate statistics?

Answer 13

Describe the distribution of scores on a single variable. (e.g what sort of scores do we see, is a particular score more common, how are the scores distributed)

Question 14

What are bivariate (and multivariate) statistics?

Answer 14

describe relationships (covariation) between two (or more than two) variables. e.g whether scores on one variable tell us something about scores on another. Looking for covariation (a relationship) is the first sign that there could be causation.

Question 15

What are inferential statistics?

Answer 15

compare descriptive statistics with what we might expect by chance alone (Subject to certain assumptions). Based on mathematical probability theory and are statements about the probability of observed results. I.E looking at whether the relationship we find are significant in some way - or just a product of chance.

Question 16

What type of statistics do you run on your data set first and what second? why?

Answer 16

Descriptive statistics, than inferential statistics.

Because you should evaluate your hypothesis first using descriptive statistics to make a tentative evaluation and than refine it further via inferential statistics.

Question 17

What is raw data?

Answer 17

The untouched data from research that has no been summaries/organised with descriptive statistics.

e.g scores from a first year psyc test = 5,6,7,7,8,8,8,9,9,10,10,11,11,11,12,12,12,12,12 etc

Question 18

What is a frequency/frequency count? (Descriptive statistics)
What are percentages?

Answer 18

A frequency count is the number of time a certain score/categorie occurs e.g there were 11 males and 39 females. These are only meaningful if you know the sample size.

This is often converted into a percentage by dividing each frequency by the total number of scores (e.g 50 participants) and then multiplying by 100 (in this case = 22% males and 78% females)

Good for categorical variables.

Question 19

What are the two types of descriptive statistics used for summarising data from continuous variables?

Answer 19

Central tendency (e.g the mean, median, mode) and variability (e.g the range, standard deviation)

Question 20

What is the standard deviation?

Answer 20

A measurement of the average (mean) variability in scores from the mean.

Question 21

What is the optimal descriptive statistics for categorical and continuous variables?

Answer 21

Categorical = percentages
Continuous = central tendency (e.g mean) accompanied by index of variability (e.g SD)

Question 22

What is the best descriptive statistic graphical representation for percentages (categorical variable)?

Answer 22

Bar chart.

Question 23

What is the best descriptive statistic graphical representation for continuous variables?

Answer 23

Histogram

Question 24

What is the interquartile range (IQR)?

Answer 24

IQR is the range of the middle 50% of scores. (thus it is not influenced by the extreme ends)

The difference between the scores at the 3rd and 1st quartiles. The third quartile is the median of the highest fifty percent of scores, while the first quartile is the median of the lowest fifty percent of scores. in otherwords 25% of scores fall below the first quartile and 50% of scores falls below the median and 75% of scores fall below the third quartile.

Question 25

What is a ‘unimodal’ distribution?

Answer 25

A distribution (of scores) with one main peak.

Question 26

What is a ‘bimodal’ or ‘multimodal’ distribution?

Answer 26

A distribution (of scores) with two, or more, main peaks.

Question 27

Is the mean a good indicator of central tendency for bimodal and multimodal distributions?

Answer 27

No. For such distributions, the central tendency is best described by noting all of the modal categories (i.e., score intervals where multiple peaks occur).

Question 28

What is a skewed distribution?

What is a symmetrical distribution?

Answer 28

Skewed = where scores tend to predominate at one end of the distribution.
Symmetrical = when the left and right hand halves of the distribution are mirror images of each other (or, at least, are approximately so).

Question 29

When a distribution is skewed such that there are more low scores than high scores, is it positively or negatively skewed? (i.e the peak is on the left)

Answer 29

Positively skewed.

Question 30

When a distribution is skewed such that there are more high scores than low scores, is it positively or negatively skewed? (i.e the peak is on the right)

Answer 30

Negatively skewed.

Question 31

What is the ‘normal distribution’?

Answer 31

A unimodal symmetric bell-shaped distribution (iwht a particular formula). Common and important for inferential statistics.

Question 32

What is the 68-95-99.7 rule for SD in a normal distribution?

Answer 32

68% of observations fall within 1SD of the mean
95% of observations fall within 2SD of the mean
99.7% of observations fall within 3SD of the mean

Question 33

Describe the SD properties of a normal distributions.

i.e what % of observations fall within 1, 2 and 3 SD of the mean

Answer 33

the 68-95-99.7 rule

68% of observations fall within 1SD of the mean
95% of observations fall within 2SD of the mean
99.7% of observations fall within 3SD of the mean

Question 34

What does a standard score or Z-score tell us?

Answer 34

How many SD a specific score is away from the mean.

A negative Z score = below the mean
A positive Z score = above the mean

Question 35

In bivariate descriptive statistics, what are the four possible combinations of scales of measurement (given dependent v. independent variable)?

Answer 35

2x categorical variables (IV x DV)
1x categorical (IV) 1x continuous (DV)
1x categorical (DV) 1x continuous (IV)
2x continuous variables

Question 36

What is the best descriptive statistic strategy for a bivariate relationship with a categorical IV and a continuous DV?

Answer 36

Difference between means (and SD).

i.e comparing the mean scores of the (continuous) dependent variable between each level of the independent variable.

Question 37

How do we get the Cohens D effect size?

and what is cohens d a measure of?

Answer 37

d = (Mean1 - Mean 2)/ SDpooled

for a conservative estimation, use the larger of the two SD.

cohens d is a measure of how many SD there is between 2 means.

Question 38

What is the best descriptive statistic strategy for a bivariate relationship with a categorical IV and a categorical DV?

Answer 38

Difference between percentages.

i.e comparing the percentages for each level of the dependent variable across each level of the independent variable.

Question 39

What effect size measure is used when comparing means? (Categorical IV, continuous DV)

Answer 39

Cohens d

i.e how many SD there is between 2 means.

Question 40

What effect size measure is used when comparing percentages? (Categorical IV, categorical DV)

Answer 40

Cohens w

OR a difference in percentage by 30% or greater = medium, and thus important, sized effect.

Question 41

What is a contingency table?

Answer 41

Used to present bivariate descriptive data regarding categorical IV and DV. Presents the frequencies and percentages for all groups.

Question 42

What is the best descriptive statistic strategy for a bivariate relationship with a continuous IV and a continuous DV?

what is the optimal graphical representation?

Answer 42

Correlation coefficient
regression coefficient

Graphical representation = scatter plot
(regression)

Question 43

On a scatter plot on which axis are the IV and DV?

Answer 43

IV = x-axis (i.e horizontal)
DV = y-axis (i.e vertical)

Question 44

What are the two important features of a scatter plot?

Answer 44

Strength and Direction

Question 45

On a scatter plot, what is a positive and a negative relationship?

Answer 45

positive relationship: people with high scores on one variable are likely to have high scores on the other.
negative relationship: people with high scores on one variable are likely to have low scores on the other.

Question 46

what is the line of best fit on a scatter plot?

Answer 46

A line drawn through the data points so that it is on average closest to all the points in the graph.

Question 47

In regression coefficients, what does a and b stand for?

Answer 47

a = value of Y when X is at 0 (i.e where the regression line crosses/intercepts the Y axis)

b = The slope of the regression line, the predicted change in the dependant variable for every 1 increase on the independent variable. (not helpful for determining strength of relationship - must be converted to standard score - i.e correlation coefficient)

Question 48

what size effect would: r = .10, .30, .50 (either - or +); be considered to be?

Answer 48

Small, Medium, Large