Rm - Analsying Recording Snd Presenting Data Flashcards Preview

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Flashcards in Rm - Analsying Recording Snd Presenting Data Deck (16):
1

Quantitative and qualitative data and strength and weaknesses of each

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

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

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

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

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

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 ?

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

Height of each bar represents the frequency of each category
When you have categoric data

10

Histogram

Like a bar chart but but bars a re together stand start at o
Continuous data e,g weight

11

Scatter graph -

Used to represent relationships between data
When conducted a correlation

12

Pie chart

Alternative to bar chart each piece represents a category of behaviour
When continues data , divide each frequency by trial frequency

13

Line graph

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

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

What is standard deviation and how to work it out

How spread out data is from the mean
Calculate mean of data set
Subtract mean from each individual value and square that difference
Calculate mean of those square difference and square root it