Week 16- Content

Question 1

What is the process of the derivation chain

Answer 1

Developing your theory:
> concepts
> assumptions about causality
This then goes down to
> measurement of psychological concepts
> auxiliary assumptions about how we get from theoretical concepts to observable data
Then link this to statistical predictions
Which can test the hypothesis

Question 2

Varying language terms need to be familiar with

Answer 2

> Outcome = response = criterion = dependent variable
Predictor = covariate = independent variable = factor
Linear model = regression analysis = regression model = multiple regression

MOST IMPORTANTLY, OUTCOME = DV; PREDICTOR = IV

Question 3

What is covariance equation?

Answer 3

variation in x * variation in y/ n - 1

Question 4

Why do we need to divide covariance by standard deviations

Answer 4

> because 2 sets of numbers can be on different scales- covariance depends on these scales
correlations easier to compare by removing scales- so divide by sd

Question 5

How can we examine variance?

Answer 5

> histograms- distribution of values in any one variable
scatterplots- association of values in two variables

Question 6

How do you code a correlation test in r studio

Answer 6

cor.test(studytwo$mean.acc,
studytwo$mean.self,
method = “pearson”)

Question 7

What data is important from a correlation test

Answer 7

Degrees if freedom
Correlation
P-value