Review of Basic Tests of Difference and Relationship

Question 1

Correlation also known as?

Answer 1

Bivariate and relationships tests.

Question 2

What is a correlation used for?

Answer 2

To examine the degree of association or relationship between variables.

Question 3

Correlation definition?

Answer 3

A numerical coefficient that indicates the extent to which 2 variables are related.

Question 4

The coefficient/number that represents the correlation is always between…?

Answer 4

-1 and +1.

Question 5

What do correlation coefficients provide?

Answer 5

Information about the strength of a relationship.

Question 6

What does a correlation coefficient of 0 indicate?

Answer 6

That the variables are uncorrelated (no relationship).

Question 7

On a graph, which variable is better placed on the Y axis?

Answer 7

The dependent variable.

Question 8

Ellipse?

Answer 8

A plane curve surrounding two focal points.

Question 9

The less the variables are scattered on a scatterplot…

Answer 9

…the greater the relationship.

Question 10

Key aspects to look at of an ellipse?

Answer 10

Incline and width.

Question 11

What % confidence do you need to have in order to determine that there’s a relationship between different variables?

Answer 11

95%.

Question 12

R value?

Answer 12

Correlation coefficient.

Question 13

P value?

Answer 13

Tells you about ‘confidence’.

Question 14

When should you produce a scatterplot of a relationship?

When can you include a trend line?

Answer 14

If it’s an important finding.

If the relationship is significant.

Question 15

The parametric statistical procedure to test for a relationship is what?

Answer 15

Pearson’s product moment correlation.

Question 16

Two main variables from Pearson’s product moment correlation test?

Answer 16

R value (correlation coefficient)
P value (probability of error associated with accepting the alternative hypothesis/HA)

Question 17

Which numbers is the P-value between?

Answer 17

0 and 1.

Question 18

In order to accept the alternative hypothesis, what does the P value need to equate to? (what is the critical P value)

Answer 18

P = 0.05 or less (Critical P value = 0.05)

Question 19

P = 0.59

What does this mean?

Answer 19

59% chance of error if you accept the alternative hypothesis.

Question 20

What do correlation coefficients provide an indication of?

Answer 20

An indication of the linear relationship between variables.

Question 21

When will the correlation coefficient underestimate the strength of a relationship?

Answer 21

When variables are related in a curvilinear way.

Question 22

What is a curvilinear relationship?

Due to this existing, what is a good idea to draw?

Answer 22

A type of relationship between two variables where as one variable increases, so does the other variable, but only up to a certain point, after which, as one variable continues to increase, the other decreases.
Therefore it is a good idea to draw a scatter plot when conducting a correlation.

Question 23

Casual relationship?

What is it also referred to as?

Answer 23

When one variable has a direct influence on another.

Referred to as cause and effect.

Question 24

A significant relationship between two variables does not mean…

Answer 24

…that there is a casual relationship.

Question 25

What is ‘the third variable problem’?

Answer 25

It could be true that A causes B, B causes A. But another variable C could also influence/’cause’ A and B.

Question 26

T-test?

Answer 26

Tells you how significant the differences between groups are. It lets you know if those differences could have happened by chance.

Question 27

Ratio scale?

Answer 27

• Has an absolute zero.
• Has orders and equally spaced units.
• No negative value.
• Values can be added, subtracted, multiplied and divided
• It has ratio scale units which allow unit conversion.

Question 28

Unit conversion?

Answer 28

E.g. 12inches = 1foot.

Question 29

Interval scale? Example?

Answer 29

Same characteristics as ratio scale but no true zero is used e.g. celsius can go below 0 and is therefore an example of interval scale however KG, for example, cannot.

Question 30

Examples of non-parametric tests?

Answer 30

• Mann-Whitney U test
• Wilcoxon signed rank test
• Kruskal-Wallis test
• Chi-squared test

Question 31

Kurtosis?

Answer 31

The sharpness of the peak of a frequency-distribution curve.

Question 32

Skewness?

Answer 32

Skewness refers to a distortion or asymmetry that deviates from the symmetrical bell curve, or normal distribution, in a set of data.

Question 33

Examples of parametric tests?

Answer 33

• Independent samples T-test
• Paired samples T-test
• One way ANOVA

Question 34

Two tailed hypothesis?

Answer 34

A two-tailed hypothesis test is designed to show whether the sample mean is significantly greater than and significantly less than the mean of a population.

Question 35

Type 1 error?

Type 2 error?

Answer 35

• The mistaken rejection of a null hypothesis as the result of a test procedure.
• A type II error is also known as a false negative and occurs when a researcher fails to reject a null hypothesis which is really false.

Question 36

Statistical inference?

Answer 36

Process of drawing conclusions about a population based upon the sample data.

Question 37

4 key features of a hypothesis?

Answer 37

1. ) Difference or relationship?
2. ) Dependent variable
3. ) Independent variable and the levels of the IV
4. ) Null and alternate versions

Question 38

When to use an independent samples t-test?

Answer 38

If you are interested in identifying differences between groups of individuals.

Question 39

On SPSS, sig. value = ?

Answer 39

P value.

Question 40

What test assumes homogenity of variance?

How do we know this assumption is met?

Answer 40

• Levene’s test.

- No peculiar F or P values.