Answer :
Answer:
Step-by-step explanation:
From the given information:
We can compute the null hypothesis & the alternative hypothesis as:
[tex]{H_o}:\text{Distribution of snowfalls in her hometown is similar to claimed percentage }[/tex]
[tex]{H_a}:\text{Distribution of snowfalls in her hometown is not similar to claimed percentage }[/tex]
The degree of freedom = n - 1
The degree of freedom = 5 - 1
The degree of freedom = 4
At the level of significance of 0.05 and degree of freedom 4,
the rejection region = 9.488
However, we can compute the chi-square X² goodness of fit test as:
months frequency (p) observed O Expected E Chi-square [tex]X^2= \dfrac{(O-E)^2}{E}[/tex]
Dec 0.2 16 16 [tex]\dfrac{(16-16)^2}{16} =0[/tex]
Jan 0.250 11 20 [tex]\dfrac{(11-20)^2}{20} =4.050[/tex]
Feb 0.200 16 16 [tex]\dfrac{(16-16)^2}{16} =0[/tex]
Mar 0.200 18 16 [tex]\dfrac{(18-16)^2}{16} =0.250[/tex]
Apr 0.150 19 12 [tex]\dfrac{(19-12)^2}{12} =4.083[/tex]
Total 1.000 80 80 8.3833
∴
The test statistics X² = 8.3833
Thus; we fail to reject the [tex]H_o[/tex] since test statistics X² doesn't fall in the rejection region.
Therefore; there is sufficient evidence to conclude that the distribution of snowfalls in her hometown is not similar to the claimed percentage.
Answer:
x^2 = 8.383;
0.05 < P-value < 0.10
Step-by-step explanation: