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Correlation
The correlation is commonly used and a useful statistic used to describe the degree of the relationships between two or more variables. Pearson's correlation reflects the degree of linear relationship between X variables which are independent and a Y variable which is independent and it ranges from positive 1 to negative 1 (+1 to -1). Below are statistics I have managed to gather which shows the relationship between the variables of wfood, totexp, income, age, nk.
The Null Hypothesis - H0: Correlation has risen by chance i.e. r = 0
The Alternative Hypothesis - H1: Correlation has not risen by chance i.e. r ≠ 0
*Exception: Reject H0 when P-value ≤ α = 0.05
Correlations: wfood, totexp, income, age, nk
wfood totexp income age
totexp -0.479 0.000
income -0.235 0.449
0.000 0.000
age 0.021 0.189 0.218
0.405 0.000 0.000
nk 0.102 0.071 0.025 0.008
0.000 0.005 0.322 0.753
Cell Contents: Pearson correlation
P-Value
a b c d e supply p 3 4 6 8 8 20 q 2 6 0 5 8 30 r 7 11 20 40 3 15 s 1 0 9 14 6 13 d 15 3 12 10 20
Level of Significance: α The main purpose of hypothesis testing is not to question the computed value of the sample statistic, but to make judgment about the difference between
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