Flashcards in Data handling And Analysis And Inferential Testing Deck (28):

1

## What are the 3 rules to follow when displaying quantitative data?

###
1)label everything

2)ensures the graph has an unambiguous (clear) title

3)when producing graphical representations for experimental data. Always plot IV on the horizontal axes and the DV (or frequency) on the vertical axes

2

## What are the types of graphs commonly used to display quantitative data?

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-Line graphs

-Tables

-Scattergrams

-Bar charts

-Histograms/frequency polygons

3

## What variables does continuous data refer to?

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Quantitative data which can be measured in a numerical way that has an infinite number of possible variables

Or

Quantitative data that can be represented in a range of numerical ways

4

## Give examples of continuous data?

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-Height

-Weight

5

## What is categorical data?

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Qualitative data that cannot be measured in a continuous way and so is set in groups

Or

Can be different values that only belong to certain groups which are discrete from each other

6

## Give examples of Categorical data

###
-Marital status

-Favourite colour

-Type of pets

7

## Describe a line graph

### It is created by plotting data as a series of points, which are then joined with straight lines. It is often used to show a trend over time.

8

## Describe tables

### Tables are often used to display descriptive statistics such as measures of central tendency (mean medium and mode) and dispersion. However, one type of table called a contingency table is used to record the frequency disruption of two or more categorical Variable. It is usually presented in matrix format. The data in each row of the table is contingent on what is in each column of the table and vice versa.

9

## Describe a scattergram

### A scattergram is used in correlational studies to see if there is a relationship between two co-variables. Scattergrams are used to show the strength and direction of correlations. Such correlations can either be positive, negative, or have no correlation.

10

## Describe a bar chart

### Represent the frequency with which each category occurs. They are therefore suitable for categorical data. The bars on a bar chart are NOT joined together and are all of an identical width.

11

## Describe a histogram

### Used to represent frequency. However, it is not suitable for Categorical data, but Continuous data, such as height and weight. The bars on a histogram are touching.

12

## Give an example of when you will use line graphs

###
-To monitor sales

-To monitor exercise trends

13

## Give an example of when you might use contingency tables

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-Gender and if they own dogs

-Twin studies

14

## Give an example of when you would use Scattergrams

###
-To show two sets of results (scores)

-Temperature and sales of ice cream

15

## Give an example of when you would use bar charts

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-Favourite colour

-Favourite tv programme

-Favourite drink

16

## Give examples of when you would use a histogram

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-Exam scores (how many people got x)

-Hours of revision done a week

17

## When are inferential statistics used?

###
To Make a generalised judgement by working out the probability that the conclusion will be wrong about the wider population.

Proving that your null hypothesis is true

18

## What is probability

### The likelihood of something happening between a scale of 0-1 (0- never gonna happen , 1 absolutely going to happen)

19

## What do inferential statistics work out?

### The probability that the null hypothesis is true.

20

## Why do psychologists use a 5% level of significance?

### It shows that there is a 1 in 20 chance that their null hypothesis is true

21

## Why would you need to use a more stringent significance level? (1% = 1 in 100 chance of the null hypothesis being true)

### When health and lives are at risk such as medicines and healthcare.

22

## What is a type 1 error?

###
When the null hypothesis is rejected when it is actually correct

Error of optimism

The probability of making a type 1 error is exactly the same as the significance level

A house is on fire but you believe that it is not

23

## What is a type 2 error

###
When you accept the null hypothesis when it is actually false

Error of pessimism

A house isn’t on fire but you flee thinking that it is

24

## Why shouldn’t you be really stringent in statistical testing?

### You may miss a relationship between the IV and DV

25

## What are the characteristics of nominal levels of measurement

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-weakest, most basic level of measurement

-Referred to as ‘categorised’ or ‘frequency’ data

-people and objects are classed together on the basis of common features and given arbitrary numbers, labels or codes.

-Mutually exclusive -only possible to belong to one catagory

26

## What are the characteristics of ordinal levels of measurement

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- Data is placed rank order which allows meaningful comparison

- Make statements about relative magnitude of scores

- Say only one value is higher than another, but not assume more than this.

- Data gathered on unstandardised, invented scales e.g attitude scales or responses

27

## What are the characteristics of interval levels of measurement

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-measurements are made on standardised scale or fixed units separated by equal distances

-Standardised personality and IQ scales are generally accepted as having equal distances between.

-Values can be positive or negative

-equal intervals are not always meaningful

28