Data Coefficients

Question 1

Line of Best Fit

Answer 1

Shows how strong a correlation is between variables

Question 2

Pearson’s Correlation Coefficient

Answer 2

Calculate how close a correlation is between two variables

Question 3

Pearson’s Correlation Coefficient Formula

Answer 3

(nΣxy) - (ΣxΣy)
r = ————————————–
√(nΣx² - (Σx)²)(nΣy² - (Σy)²)

x = variable 1
y = variable 2
Σ = sum of
n = number of data entries of each variable
r = the correlation coefficient

Question 4

Understanding the Correlation Coefficient

Answer 4

r = 1: correlation is perfectly positive - all points are on the line of best fit, sloping up from left to right

r = -1: perfectly negative - all points are on the line of best fit, sloping down from left to right

r = 0: no correlation - points are all over with no line of best fit

Correlation coeff can only be between 1 & -1

Question 5

Coefficient of Determination

Answer 5

Calculates the proportion to which a change in Y is determined by a change in X

Question 6

Understanding the Coefficient of Determination

Answer 6

1 = perfect correlation - change in Y value is solely down to the change in X value

0 = no correlation - change of X value had nothing to do with the change in Y value

Question 7

Coefficient of Determination Formula

Answer 7

r²

r = the correlation coefficient

Question 8

Spearman’s Rank Correlation Coefficient

Answer 8

Determines the correlation, if any, between the rankings of two distributions. The closer to 1, the closer the correlation

Question 9

Spearman’s Rank Correlation Coefficient Formula

Answer 9

6Σd²
Rs = 1 - ——————
n(n² - 1)

Rs = Spearman's Rank
n = the number of points in the data
d = the difference between rankings
Σ = sum of

Question 10

Spurious Connection

Answer 10

Where two unrelated variables have the same trend pattern. Always verify the connection - how likely is it that the variables would influence each other?

Question 11

Extrapolating

Answer 11

Making assumptions about results outside the data set