When we carry out a chi-square goodness-of-fit test for a normal distribution, the null hypothesis states that the population: a. Does not have a normal distribution
b. Has a normal distribution
c. Has a chi-square distribution
d. Does not have a chi-square distribution
e. Has k-3 degrees of freedom

Option B

Step-by-step explanation:

The null hypothesis for a chi-square goodness of fit test states that the data are consistent with a specified distribution.

While the alternative hypothesis states that the data are not consistent with a specified distribution.

In this case study, the test is for a nose distribution. Thus the null hypothesis would be that the population has a normal distribution.

connie < felicia < stew

step-by-step explanation:

stew:

we need to find the slope

m = (y2-y1)/ (x2-x1)

    = (2650-795)/(10-3)

    = 1855/7

265 words per minute

connie:

we need to find the slope

m = (y2-y1)/ (x2-x1)

we have two points (0,0) and (4,800)

m = (800-0)/(4-0)

  m = 800/4

    200 words per minute

felicia:

260 words per minute

200< 260 < 265

connie < felicia < stew