Week 2/3- More Principles, sampling, measurement and hypotheses

Question 1

What is validity?

Answer 1

when we are successful in measuring what we want to measure, we will have no measurement error

Question 2

what is random error?

Answer 2

When external factors influence a respondents response to a question

Question 3

can you do much to prevent random error?

Answer 3

no

Question 4

what is systematic error?

Answer 4

the way we ask our questions influences the respondents answer eg leading question

Question 5

can you do much to prevent systematic error?

Answer 5

yes

Question 6

what is test- retest reliability?

Answer 6

measuring something twice to make sure the outcomes are the same. demonstrates the effectiveness of the random sampling

Question 7

how does the population of interest affect validity?

Answer 7

You need to ask questions to the right people

Question 8

what is probability sampling?

Answer 8

every individual in the population has an equal chance of being included in the sample. Also called random sampling

Question 9

what is multi-cluster sampling?

Answer 9

when you split the population into strata and then randomly select various strata from within the initial strata

Question 10

what are the benefits of multi-cluster sampling?

Answer 10

reducing costs and reducing travel time

Question 11

do larger sample sizes provide more accurate findings than smaller ones and why?

Answer 11

yes and smaller sample sizes have a greater probability of including outliers

Question 12

when our sample size gets larger, what happens to our confidence interval?

Answer 12

it gets smaller

Question 13

what is a type II error as a result of a small sample size?

Answer 13

where a false null hypothesis is rejected

Question 14

what are the two implications of a smaller sample size?

Answer 14

1) decrease in statistical power: Increases the probability of type II errors
2) Missing values: not all respondents reply to all of the questions

Question 15

what is a confidence interval?

Answer 15

a plus or minus figure indicating the range that an estimated statistic probably falls between. Also called margin of error

Question 16

what is the confidence level?

Answer 16

tells you how sure you can be that your findings would be repeated if you did the survey again

Question 17

what is a coverage error?

Answer 17

occurs when the list from which sample members are drawn from does not accurately represent the population that you are interested in

Question 18

what is a sampling error?

Answer 18

the difference between the estimate produced when only a sample of the population is surveyed and the estimate produced when everyone in a population is surveyed

Question 19

what is a non-response error?

Answer 19

the difference between the estimate produced when only some of the sample respond compared to when everyone in the sample responds. eg some people didn’t participate because the survey was online etc

Question 20

what is a measurement error?

Answer 20

the difference between the estimate produced and the true value because respondents gave inaccurate answers to the survey questions. This can happen due to social desirability bias.

Question 21

what is a measurement error?

Answer 21

the difference between the estimate produced and the true value because respondents gave inaccurate answers to the survey questions. This can happen due to social desirability bias.

Question 22

what is a type I error?

Answer 22

Detecting a non-existent effect

Question 23

what are descriptive statistics?

Answer 23

used to describe the characteristics of data- tend to be uni-variable (one variable)

Question 24

what are analytical statistics?

Answer 24

describe the relationship between different variables- tend to be bi-variate or multi-variate

Question 25

what is the trimmed mean?

Answer 25

the same as the mean but the top 5% results and the bottom 5% results are not included

Question 26

What type of statistics does the measure of centrality belong too?

Answer 26

Descriptive

Question 27

give examples of analytic categories

Answer 27

age and height
demographics and purchasing behaviour
job satisfaction
Customer satisfaction and repeat purchasing

Question 28

what are correlation variables?

Answer 28

the variables are related but we cannot say that one causes the other

Question 29

what are causation variables?

Answer 29

the variables are related and changes in one variable causes changes in the other

Question 30

what are the four necessary pre-conditions for causality?

Answer 30

1) Temporal precedence: the presumed cause must occur before the presumed effect
2) Association: Variation in the presumed cause must be related to that in the presumed effect
3) Isolation: No other explanations of causality between two variables
4) The direction of the causal relationship is correctly specified

Question 31

why is the dependant variable called the dependant variable?

Answer 31

Because it is dependant on the result of the independent variable

Question 32

What is standard deviation?

Answer 32

How much the results were spread out around the mean result

Question 33

what are the four steps in hypothesis testing?

Answer 33

1) Specify the null hypothesis in a statement of no effect or relationship
2) Specify the critical value ( the p-value blow which we reject the null hypothesis) - this is usually <0.05
3) Decide on the most appropriate test to use and run that test
4) Use the resultant p-value to reject or accept the null hypothesis

Question 34

What are the for outcomes to a hypothesis test?

Answer 34

1) There really is no relationship present and that’s what our test found
2) There is no relationship present but our test says there is one- Type I error
3) An effect is present and our test supports this
4) An effect is present but our test suggests there isn’t- Type II error

Question 35

how can we reduce the probability of both Type I and II errors?

Answer 35

Increasing the power of our statistical test