Flashcards in Rm - Analsying Recording Snd Presenting Data Deck (16):

1

## Quantitative and qualitative data and strength and weaknesses of each

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Data in form of numbers

S- easy to analyse we can easily compare results over two conditions, w- doesn't gives us any reasoning behind data .lacks detail

Data in from of words

S- gives details. Reasoning behind results

W- difficult to analyse , we can compare results over two conditions find it hard to draw conclusions

2

## Primary and secondary data strengths and weaknesses of each

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Researcher collects data themselves

S- current reliable , controlled tailored to you

W- time consuming , biased and costly

Secondary - data collected by somebody else which you use

S- less time consuming , less bias and cheaper

W- may not be current, not reliable less control

3

## Ordinal data and examples

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Data put in order e.g. Put people in order in terms of height small to tall

Rating likely scale semantic differential scale

4

## Nominal data and examples

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Most basic type and data put into to categories e..g height small normal and tall I yes no repsonses.

5

## Interval data -

### Data that uses an standardises scale. Measuring people height in cm , temperature or score on a test

6

## What is the mean and its advantages and disadvantages

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Shows the average score of a data set add all data together divide this some by how many bits of data you have.

A- most accurate uses amount of every score.

W- influenced by outliers

7

## What is the median

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Middle number of a data set put all numbers into chronological order to find middle value

A- useful for extreme scores not affected by outliers w- time consuming does not use all data wastes it

8

## Mode ?

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Piece of data which occurs the most in a set of data

A- with reasonable sized sample it can give accurate idea of average , not influenced by extreme scores

W- wastes data tow modes are diverse don't provide us with accurate data

9

## Bar chart what is it and what is it used for

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Height of each bar represents the frequency of each category

When you have categoric data

10

## Histogram

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Like a bar chart but but bars a re together stand start at o

Continuous data e,g weight

11

## Scatter graph -

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Used to represent relationships between data

When conducted a correlation

12

## Pie chart

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Alternative to bar chart each piece represents a category of behaviour

When continues data , divide each frequency by trial frequency

13

## Line graph

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Alternative to a histogram line connects each dot

To show how something changes over time

14

## Range

### Difference between highest value and lowest value

15

## What is variance and how do you work it out

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How spread out data is

All late mean , for each individual value subtract the mean and square result , calculate mean of those square differences

16