Inferential Statistics/maths Flashcards

1
Q

Test used with nominal data, independent measures design

A

Chi square

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2
Q

Test with ordinal data and independent measures design

A

Mann-Whitney U-test

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3
Q

Test with nominal data and repeated measures/matched participants

A

Binomial sign test

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4
Q

Test using ordinal data and repeated measures/matched participants design

A

Wilcoxon signed ranks

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5
Q

Test used ordinal data correlation study

A

Spearman’s Rho

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6
Q

Test used interval/ratio correlation study

A

Pearson’s product moment

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7
Q

Para and non parametric tests

A

Parametric tests are used when there is:
Interval/ratio level data (t tests and Pearson’s product moment)
A normal distribution of data
Similar variances between results from the different conditions (homogeneity of variance)

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8
Q

First step chi square

A

Add up row and column totals and overall totals

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9
Q

Second step chi square

A

Write in the observed frequency

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10
Q

Step 3 chi square

A

Work out expected frequency

Row total X column total divided by overall total

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11
Q

Fourth step chi square

A

Observed frequency minus expected frequency

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12
Q

Fifth step chi square

A

Square the observed frequency minus expected

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13
Q

Sixth step chi square

A

After you square the observed-expected

You divide this answer by the expected frequency

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14
Q

Seventh step chi square

A

X squared = add up last column

Last column was where you divide by the expected frequency

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15
Q

Chi square: X squared from the table is…

A

Calculated value

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16
Q

Chi square: how to calculate degrees of freedom

A

(Number of rows-1) X (number of columns-1)

Always 1

17
Q

Chi square: how do you find critical value on the table

A

Look at level of significance needed at the top (columns)

Look at degrees of freedom at the side (rows)

18
Q

For chi square and Spearman’s Rho, what’s needed to be significant? (Confirm alternative hypothesis)

A

Calculated value bigger than critical value

19
Q

Binomial sign text what’s needed to show significant difference? (Confirm alternative hypothesis)

A

Critical must be bigger than calculated value

20
Q

Measures of dispersion

A

Range, variance, standard deviation

21
Q

Variance method

A
  1. Calculate mean
  2. Original score - mean (gives ‘d’ difference)
  3. Square it (d2)
  4. Add all new d squared values and divide by number of participants minus 1
    (Like mean but minus one from number of participants before you divide)
22
Q

Standard deviation method

A

Square root of variance

23
Q

Difference between bar graph and histogram

A

Gaps in bar charts (non continuous data)
Histogram used with interval/ratio data

Histogram Y axis frequency density 
Frequency density= frequency/ class width 

Frequency given by area of the bar, not height in histogram
Bar charts bars can be unrepresentative especially in unequal categories

24
Q

Binomial sign test method

A
  1. Put plus or minus indication direction of difference
  2. Add up least frequent sign to get calculated value
  3. Use level of significance+one/two tailed hypothesis (column) and number of participants (rows) to find critical value
  4. To show level of significance (confirm hypothesis) critical value must be bigger than calculated value
25
Experiment hypothesis v correlation hypothesis language
Experiment ‘difference’ | Correlation ‘relationship’
26
Strength of variance
Takes into account all data collected
27
Histogram eval
S- representative as shows correct proportions
28
Bar chart eval
W- unrepresentative bars don’t always show correct proportions
29
How to work out frequency density for histogram
``` Frequency divided by class width (This is how tall bar will be) ```
30
What needs to be included for statement of significance
- Operationalised hypothesis - level of significance (eg. P smaller or equal to 0.05) - explain why (is calc value higher or lower than critical)
31
Find ratios of given amount | Eg. 2:7 of £45
``` Divide value by total rations Multiply by ration you want to find out Eg. 45/9 = 5 5 X 7 = 35 5 X 2 = 10 ```
32
Find fraction of given amount
Divide by denominator | Multiply by numerator
33
Pie chart
Data for each group divided by total data X 360 = each sector
34
Conversion between %, fractions & decimals
% into decimal = divide by 100 | % into fraction = over 100 then simplest form