How can i solve this?
1 answer:
You might be interested in
Answer:
is an attachment
test statistic = 9.87
p value is less than 0.01
Not all means of the three assembly methods are equal
Step-by-step explanation:
the anova table is an attachment
total number of methods = k = 3
number of observations n = 30
for treatment, df = 3-1 = 2
for error, df = 30 -3 (n-k) = 27
sst = 10800, sstr = 4560, sse = 10800-4560 = 6240
we find the mean of squares for error
sse/df of error = 6240/27 = 231.11
mean of squares for treatment = 4560/2 = 2280
test stat
F = 2280/231.11
= 9.8654
using f distribution table;
alpha = 0.05
df = 2 , 27
we get 3.35
h0; no difference in mean
h1; there is difference
9.87 > 3.35 so we reject H0, there is difference in means. all are not equal.
pvalue calculation
using excel,
FDIST(9.8654, 2, 27) = 0.0006078
p value is less than 0.01
we conclude that a. Not all means of the three assembly methods are equal
Answer:
a. The linear function is given by,
y = 60x + 30 [y is in $ and x is in hour and x ≥ 0.5]
= 60 [for x < 0.5]
b. The total cost of the repair job is, $ 675 .
Step-by-step explanation:
Let, the linear function describing garage charge( y in $) and no. of hours of repair job ( x in hour) be,
y = mx + c [for x ≥ 0.5] -----------(1)
where, m is the slope of the line and c is the y intercept.
Now ,
m =
= 60 ----------------(2)
Now, putting the value of m and the point (x,y) = (0.5, 60) in (1), we get,
$
⇒ c = 30 ----------------- (3)
Hence, the linear function is given by,
y = 60x + 30 [y is in $ and x is in hour and x ≥ 0.5] ------------(4)
= 60 [for x < 0.5]
Now, putting
x = 4 hr 15 min
= hour
= 4.25 hour in (4), we get,
[in $]
= $ 285
So, the total cost of the repair job,
= $ (285 + 390)
= $ 675