Sadie's Lecture 4

Question 1

What is “inferential statistics”?

Answer 1

Fan: Inferential statistics is the process of drawing conclusions from data that are subject to random variation eg. Observational errors or sampling variation

Google: Inferential statistics use measurements from the sample of subjects in the experiment to compare the treatment groups and make generalizations about the larger population of subjects. There are many types of inferential statistics and each is appropriate for a specific research design and sample characteristics.

Question 2

_____ _____ helps us decide whether we can generalize about a larger population based on the characteristics of the observed sample

Answer 2

inferential statistics

Question 3

The process of drawing inferences, making predictions and testing significance are examples of ______ ______

Answer 3

inferential statistics

Question 4

True or false: Statisticians think about events in terms of “change, randomness, errors and distribution”… dealing with issues of uncertainty or events with unknown reasons.

Answer 4

TRUE

Question 5

What does statistical significance testing identify?

Answer 5

The probability that our findings can be attributed to chance.

Question 6

If a result of statistical significance testing is unlikely to have occurred by chance, it is called:

Answer 6

Statistically significant.

Question 7

A statistical significance test used when both the dependent and independent variables are nominal-level… eg yes/no , m/f

Answer 7

Chi-Square test

Question 8

What test should you do if you want to know if knowing the value of one variable helps to estimate the value of another variable?

Answer 8

Chi-Square test

Question 9

After completing a Pearson Chi-Square, the Asym. Sig (Asymptotic significance) is 0.03. Is the relationship between the two variables significant?

Answer 9

Yes, If your “Asym. Sig.” number is less than 0.05, the relationship between the two variables in your data set is statistically significant. If the number is greater than 0.05, the relationship is not statistically significant.
- Not a result of random chance

Question 10

What is a null hypothesis (Ho)?

Answer 10

Fan: the hypothesis that there is no validity to the tested variables.

Google: the null hypothesis assumes there is no relationship between two variables and that controlling one variable has no effect on the other

Question 11

What does the “level of statistical significance” refer to?

Answer 11

The probability of a false rejection of the null hypothesis in a statistical test

Question 12

What are the three common levels of statistical significance?

Answer 12

Common significance levels are 0.10 (1 chance in 10), 0.05 (1 chance in 20), and 0.01 (1 chance in 100).

Question 13

What is a nondirectional hypothesis?

Answer 13

A hypothesis that does not specify whether the predicted relationship will be positive or negative

Question 14

What are two tailed tests used for?

Answer 14

Non directional hypotheses.

Question 15

Generally, statistical significance is a measurement of Type ___ error.

Answer 15

Type 1 Error

Question 16

What is a type 1 error?

Answer 16

A error we risk committing whenever we reject a null hypothesis. It occurs when we reject a true null hypothesis.
For example…. False positive.

Question 17

What is a type 2 error?

Answer 17

An error we risk committing whenever we fail to reject the null hypothesis. It occurs when we fail to reject a false null hypothesis.
Eg. False negative

Question 18

A false positive is an example of which error type?

Answer 18

Type 1 error

Question 19

A false negative is an example of which error type?

Answer 19

Type 2 error

Question 20

True or false…. Every decision based on statistical testing risks one error or the other.

Answer 20

TRUE, for example criminal justice. (guilty or not?)

Question 21

Why reject a null hypothesis instead of proving a hypothesis?

Answer 21

Because The Falsification Principle, proposed by Karl Popper, is a way of demarcating science from non-science. It suggests that for a theory to be considered scientific it must be able to be tested and conceivably proven false. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

Question 22

Hellen has a null hypothesis that states “each chocolate bar has 70g of nuts” and after she tested it, the P value is 0.18…. What does this mean?

Answer 22

This P value of 0.18 means that the evidence is not significant enough to reject the null hypothesis. The P value would have to be smaller than 0.05 to provide good evidence that it wasn’t just luck, and that Hellen’s chocolate bars did NOT have 70g of nuts.
Remember…. P IS LOW, NULL MUST GO. (reject the null hypothesis.)