Sampling

Question 1

What is sampling?

Answer 1

Selecting a subset of participants/objects from a larger group or population.

E.g. You want to know how tesla drivers feel about the electric cars?

SAMPLE MUST BE REPRESENTITIVE OF THE POPULATION

Question 2

What is probability sampling?

Answer 2

used in quantitive analysis.

Question 3

What is non-probability sampling?

Answer 3

participants selection based on the discretion of the researcher.

Question 4

How to choose the correct sampling methodology?

Answer 4

Always understand research Aims and Objectives

Question 5

Describing the sample

Answer 5

Interested in the details of your samples
Mean, median, Mode, standard deviation, skewness (how symmetrical the numbers are)
Provide micro and macro level view of data
Help spot potential errors in the data
Help inform which inferential statistics to use

Question 6

Quantitative analysis

Answer 6

Inferential statistics
Aim to make inferences/predictions about the populations
E.g. differences between groups
Relationships between variables
Allows you to connect the dots on the population view based on what you see on your data

Question 7

What is descriptive statistics?

Answer 7

summarise and organise the data within the sample.

Question 8

What is inferential stats?

Answer 8

use sample to make inferences about the data.

Question 9

Different types of Inferential statistics

Answer 9

t-test: compare means of two groups

Analysis of variance (ANOVA): compare means of more than two groups

Correlation analysis: assess relationship between variables

Regression analysis: measures cause and effect