# Statistical Significance Test

The analysis of variance (ANOVA) table of the output table # 4 in Figure 4 provides information on the statistical significance of the relationship between the fuel cost and the distance. This step on the statistical significance test includes four steps, which has been discussed in earlier module 1, 2, and 3. The statistical significance tests follow the four steps provided below.

# Hypothesis

[In regression analysis in this example, is there a statistical relationship between the fuel cost and the distance?]

Null Hypothesis: β1 = 0

[zero slope = no functional relationship, meaning that fuel cost does not change with the distance]

Alternative Hypothesis: β1 ≠ 0

[There is a functional relationship between the fuel cost and the distance]

# Appropriate Method

Simple linear regression analysis is the appropriate method for this situation. Any statistical software, including MS Excel and Minitab can be used for the simple linear regression analysis. Minitab version 19 was used in this analysis.

# Statistical Results

Null hypothesis is rejected due to the p-value (=0.000) is less than the level of significance (alpha = 0.05).

[p-value is defined by the observed probability of the null hypothesis to happen]

# Contextual Explanation

There is a statistically significant functional relationship between the fuel cost and the distance traveled.