Problem 6-1: Observations on two random variables X and Y are presented in the following table:
a / test the hypothesis for equality of the two variances;
b / check the hypothesis of no correlation.
Assume a confidence interval b = 0.95.
Problem 6-2: We look for a mathematical dependence of the snow
cover - Y, as a function of altitude - X in the Alps. For this
purpose, a sample of 8 different locations, often visited by
tourists, was selected. The data are presented in the following
table:
a / to build a linear regression model
b / to assess the accuracy of the model by a coefficient of
determination;
c / use the constructed model to predict the expected snow cover at
an altitude of 3.55 thousand m.

Problem 6-1:
(a) The hypothesis being tested is:
| Null hypothesis | H₀: σ₁² / σ₂² = 1 |
| Alternative hypothesis | H₁: σ₁² / σ₂² ≠ 1 |
| Significance level | α = 0.05 |
| Method | Test Statistic |
DF1 | DF2 | P-Value |
| F | 13.46 | 7 | 7 | 0.003 |
The p-value is 0.0003.
Since the p-value (0.003) is less than the significance level (0.05), we can reject the null hypothesis.
Therefore, we can conclude that the variances are not equal.
(b) The hypothesis being tested is:
H0:
= 0
Ha:
≠ 0
| Source | SS | df | MS | F | p-value |
| Regression | 3.2737 | 1 | 3.2737 | 1.84 | .2240 |
| Residual | 10.6863 | 6 | 1.7811 | ||
| Total | 13.9600 | 7 |
The p-value is 0.2240.
Since the p-value (0.2240) is greater than the significance level (0.05), we fail to reject the null hypothesis.
Therefore, we cannot
conclude that
≠ 0.
Problem 6-1: Observations on two random variables X and Y are presented in the following table:...