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Flashcards in Quant: Lecture 1 Deck (22):
1

What makes psychology a science?

The fact that it gathers empirical data and measures/treats data consistently. It often gathers numerical data, that is then interpreted and not just calculated.

2

What does qualitative data gather?

Verbal reports, aka speech or texts that can be used for subjective interpretation.

3

What does quantitative data gather and how?

It operationalises concepts by gathering numerical data. It usually does this via objective pre-arranged measurement that can be numerical or nominal.

4

Describe nominal data

Data that measures discrete categories that aren't ordered by gathering frequencies or tally charts. From this you can work out percentages of the results.

5

Describe numerical data

Data that gathers continuous, ordered scales which are sets of numbers increasing in value. It can be subjective and objective. There are 3 types; ratio, interval and ordinal.

6

Describe ratio data

Data that's measured on a continuous scale with equal gaps between adjacent points. The zero point is the absolute zero, there is no lower value. For example, reaction time, heart beat, number of items recalled etc. It gathers objective data.

7

Describe interval data

It gathers data by using a well established physical state like temperature. There are equal intervals between adjacent points and there can be a value lower than zero. This measurement is also objective.

8

Describe ordinal data

This data collection is subjective as it relies on human estimation in terms of rating events and/or behaviour. For example, attraction scales. They have arbitrary end points and the adjacent points aren't necessarily equal. The ratings can be ordered and it usually measures conceptual variables aka statements that you can rate.

9

How do you gather the mean?
Evaluate this method.

_
x = Ex/n. You add up all the scores and divide by the number of variables.
It's a precise method but it can be easily distorted by outliers. It's not necessarily equal to any original values and it avoids spurious accuracy. This method describes the central tendency.

10

What does standard deviation measure?
What makes the value larger?
Define dispersion
Define variability

It measures the dispersion of data.
The more deviation from the mean in your results will result in a larger SD.
The degree of variability of your scores.
The range of data around the mean.

11

How do you calculate SD?

First, you work out the mean. The you do x - the mean for each piece of data. Then square each of these results and total it to get E(x-mean)2. Then you do n-1. Finally, put all the data into the formula and divide E(x-mean)2 by n-1 and get the square root of that answer. After this you need to find out whether it is significant.

12

How should you word your answer of SD?

IV and DV was (M=***, SD=***).

13

Describe what a normal distribution should look like, with statistics.

It should be bell shaped, with the mean at the peak of the bell. 34.13% of the results should be in the +1 SD area and the -1 SD area. 68.26% of results should fall within +- 1 SD. 95.4% should fall between +- 2 SD.

14

Describe confidence intervals

It's a calculation that tells you how representative your results are to the general population. 95% CI is the range of scores around the mean that will include the population mean. To find out this range, you + or - the t value from the mean. Then you find the square root of n, and divide this by the SD. Finally, you times the mean+-t by this number. From this, you find the upper and lower bound CI by +- the mean and the CI. We can then be 95% sure that the true mean lies between these values.

15

How should you word your answer for CI?

CI95% = mean +- CI

16

How should you present your data?

You should present it clearly, with no ambiguous labelling or poor titles. The tables and figures should make sense on their own and the message should be conveyed effectively.

17

How should you present tables?
What are the 4 types of figures you would use?

Include the table number (Table 1.) and title above the table. Give the columns and rows clear headings and only use horizontal lines. Don't use excessive decimal places and add explanatory notes under the table if needed.
Histogram, scatterplot, frequency bar chart and bar chart with error bars.

18

Describe the use and presentation of a histogram

It's used to examine the distribution of scores on a continuous numerical variable. The horizontal axis displays the continuous variable and the bar heights show frequencies. They show the distribution shape of large samples. It shows the normal distribution and allows the true mean and skews to be examined.
A positively skewed distribution peaks towards the left side and negative towards the right. Both axis should be labelled with a figure number and title below the figure and there should be 50+ participants.

19

Describe the use and presentation of a frequency bar chart.

It's used to examine the distribution of scores on a categorical variable. It allows you to compare relative popularity of responses between groups. Always use patterns instead of shading and put the figure number and title below the figure. Don't refer to your figure as a graph and use a legend inside the frame if needed to explain the graph.

20

Describe the use and presentation of a bar chart with error bars

It's used to show means and SDs of a continuous variable for different groups on a categorical variable. The bar consist of the mean and the error bars are +-1 SD.

21

Describe the use and presentation of a scatterplot

It's used to show the relationship between two variables measured via a continuous numerical variables.

22

When should you use a table, figure or text?

Text = Less than 3 participants
Table = 4-20 participants
Figure = 20+ participants