Psychology > 4.2.3.3 Inferential Testing > Flashcards

4.2.3.3 Inferential Testing Flashcards

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1
Q

What are descriptive statistics?

A

Refers to graphs and numerical data that provide a basic analysis of data and identify trends in the data set. They include graphs, tables, measures of central tendency and measures of dispersion.

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2
Q

Why are descriptive statistics limited?

A

They cannot tell us whether to accept or reject the null hypothesis based on the significance of the data

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3
Q

What are inferential statistics?

A

Statistics which determine whether results are statistically significant, and the probability that they are due to chance. This determines whther we accept or reject the null hypothesis and whether we can conclude that the change in the IV caused the change in the DV.

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4
Q

What do we do if our results are statistically significant?

A

We can reject the null hypothesis

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5
Q

What do we do if results are statistically insignificant?

A

Accept the null hypothesis

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6
Q

What does the null hypothesis generally state?

A

That any difference/change in the variables is due to chance

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7
Q

What is the common level of significance in psychology?

A

P <= 0.05
Means that there is a less than 5% chance that the results are due to chance

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8
Q

Why do we use 0.05 as the level of significance in psychology?

A

Because it is seen as a balance between a type 1 and a type 2 error.

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9
Q

What is probability?

A

A measure of the likelihood that a particular event will occur

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10
Q

Define significance

A

A statistical term that tells us how certain we are that a difference or correlation exists between the IV and the DV

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11
Q

What is a level of significance?

A

The probability level at which the psychologist can claim to have discovered a significant difference between the IV and DV to be able to conclude that the results are not due to chance.

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12
Q

Do statistical tests work on probability or certainty?

A

Probability- can never be 100% certain that the change in the IV caused the change in the DV

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13
Q

What do we do if the probability is less than or equal to 0.05?

A

Less than 5% probability that the results are due to chance so we reject the null hypothesis and accept the alternative hypothesis.

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14
Q

What do we do if the p value is more than 0.05?

A

More than 5% probability that the results are due to chance so we accept the null hypothesis and reject the alternative hypothesis.

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15
Q

What is it called if the researcher uses a level of significance lower than 0.05 eg. 0.025?

A

They are using a more stringent level of significance

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16
Q

Why would researchers use a more stringent level of significance?

A

If they need to be even more certain that their results are not due to chance eg. If they are challenging a well-established theory
They want to eliminate as much chance as possible

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17
Q

When does the level of significance get established?

A

Before starting the investigation- means that the results cannot dictate the level of significance

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18
Q

What is an alternative hypothesis?

A

Predicts that the results occur due to the variables being studied (directional or non-directional)

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19
Q

What is a critical value?

A

A numerical boundary in a statistical test that determines whether the result is significant (each test has its own table of critical values)
The calculated value from the statistical test is compared to the critical value to test for significance

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20
Q

What is considered when deciding which critical value to use?

A

Whether the hypothesis is directional or non-directional (one or two tailed)
The number of participants
The level of significance

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21
Q

What happens to probability for a non-directional test/two tailed?

A

Because you are considering the effect of chance in both directions

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22
Q

What is a type 1 error?

A

When the null hypothesis is rejected and the alternative hypothesis is accepted when it should have been the other way around. This is also known as a false positive, as the researcher claims to have found a correlation when the results were due to chance in reality.

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23
Q

What causes type 1 errors?

A

Using a level of significance which is too lenient (not being cautious enough).

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24
Q

What is a type 11 error?

A

When the null hypothesis is accepted and the alternative hypothesis is rejected when it sound have been the other way around. This is also known as a false negative as the researcher claims that the results were due to chance, but they are actually significant in reality.

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25
What causes type 11 errors?
Using a level of significance that is too strict (being too cautious) Poor research deigns Faulty sampling Random errors
26
What are the 3 factors that choice of statistical test depends on?
Whether the researcher is looking for a difference or a correlation (association) The level of measurement of the data The experimental design used
27
What are the 2 related experimental designs?
Repeated measures and matched pairs -because participants in each condition are related in some way
28
What is the unrelated experimental design?
Independent groups -different participants so are not related in any way
29
What are levels of measurement?
Different categories of quantitative data
30
What are the 3 levels of measurement?
Nominal, ordinal, interval
31
Describe nominal data?
Data is represented in the form of categories and people or events are sorted into them. Sometimes referred to as categorical data Eg. If you sorted people into those who do and dont like psychology It is discrete so each item can only appear in one category, and there is no overlap between categories
32
What is a limitation of nominal data?
Provides us with the least amount of data about the participants of all of the levels of measurement. Tells us only that one participant is different from another, but nothing about the extent of the difference.
33
Describe ordinal data?
When the data is ordered in some way Eg. Rating how much people like psychology on a scale from 1-10 There is not equal intervals between each unit, so units of measurement are not of equal, definable size (eg. Two people who give psychology an 8 cannot guarantee that they like it exactly the same amount). They tend to be subjective rather than objective so the data lacks precision
34
Limitation of ordinal data?
Does not tell us difference between units Lacks objectivity and precision so is referred to as unsafe data Limited use for statistical testing (converted to ranks instead)
35
Describe interval data?
Based on continuous numerical scales with units of equal and precisely definable size. Advantageous as more detail is obtained (how much results differ). Eg. Height, reaction time Measured using instruments that produce data as public units- accepted units of measurement eg. cm or seconds
36
What is a strength of interval data?
Provides us with the most information, including the order of results and how different they are form each other.
37
Why do we use certain measures of central tendency/dispersion for different levels of measurement?
Because they are more appropriate for the type of data
38
What measure of dispersion/central tendency do we use for nominal data?
N/A- as data is categorical Mode
39
What measure of dispersion/central tendency do we use for ordinal data?
Range Median (cant be standard deviation or mean as the intervals between the measurements are not of equal size)
40
What measure of dispersion/central tendency do we use for interval data?
Standard deviation Mean
41
What is a parametric test?
A statistical test which is powerful because it is precise and sophisticated. This is because they are more sensitive to fluctuations in the data, so are b ale to detect significance within some data sets that non-parametric tests cannot. They also consider the size of the differences not just the ranks.
42
What are the 3 criteria for using a parametric test?
Interval data Normal distribution (population would be expected to show normal distribution) Homogenous variances
43
How can we ensure that data is normally distributed?
Plot data on a frequency distribution bar graph and see if it shows a bell shaped curve Calculate all measures of central tendency and check that they are all similar
44
What is homogenous variance?
The set of scores in each condition should have a similar dispersion or spread around the mean.
45
How is homogenous variance determined?
Comparing the standard deviations squared in each condition to check they are similar Calculating the range in each condition to check they are similar.
46
When can IQ tests be classed as interval data?
When the questions are standardised
47
What 3 factors does the choice of a statistical test depend on?
1. Whether the researcher is looking for a difference (experiment) or correlation (between 2 co-variables) 2. Level of measurement- whether the data is nominal, ordinal or interval 3. Experimental design- independent groups, repeated measures or matched pairs (related or unrelated) Note: correlational studies don’t have an experimental design
48
What are the 8 statistical tests?
Chi-square Sign test Mann-Whitney U Wilcoxon Spearman’s rhombus Unrelated t-test Related t-test Pearson’s r
49
When would you use the chi square test?
1. Test of difference, unrelated design, nominal data 2. Test of correlation, nominal data
50
When would you use the sign test?
Test of difference, related design, nominal data
51
When would you use the Mann-Whitney U test?
Test of difference, unrelated design, ordinal data
52
When would you use the Wilcoxon test?
Test of difference, related design, ordinal data
53
When would you use the spearman’s rho test?
Test of correlation, ordinal data
54
When would you use the unrelated t-test?
Test of difference, unrelated design, interval data
55
When would you use the related t-test?
Test of difference, related design, interval data
56
When would you use the pearson’s r test?
Test of correlation, interval data
57
What are the 3 parametric tests?
Unrelated t test Related t test Pearson’s r (For interval data)
58
Which tests need a calculated value less than or equal to the critical va;lie to be significant?
Sign test, Mann-Whitney U, Wilcoxon
59
Which tests need a calculated value that is more than or equal to the critical value to be significant?
Chi-square, spearman’s rho, unrelated t test, related t test, pearson’s r
60
What is the mnemonic to remember the statistical tests table?
Can Simon Cowell Make William Shakespeare Understand Received Pronunciation
61
What is the calculated value?
The value of a test statistic calculated for a particular data set
62
What is a critical value?
When testing a hypothesis, this is the cut-off point between acceptance of and rejection of the null hypotheiss
63
What is the N value?
The number of participants included in the study (A value for each group if used independent groups)
64
What are degrees of freedom?
The number of values in the final calculation of a statistic that are free to vary
65
Which tests use degrees of freedom rather than an n value?
Chi-squared, pearson’s r and unrelated and related t-tests
66
What is a contingency table?
A table that displays nominal and independent data
67
Describe the steps involved to conduct the sign test?
Will be given data for each participant and their scores for each variable 1. Subtract one score from the other for each participant (doesn’t matter which way around as long as you do it the same way around for all participants) 2. The S value (calculated value) is the frequency of the least occurring sign (+ or -) 3. The N value is the number of participants - the number that have equal scores for the variables 4. If the s value is less than or equal to the critical value, then the results are significant.
68
what is the difference between correlation and association?
Associations tell us that two variables are connected but not in what direction or how strongly. Whereas correlations tell us the strength and direction of a relationship between variables in a more scientific way
69
Which level of measurement is used in a correlation?
ordinal or interval data
70
which level of measurement is used in a study of association?
nominal
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