Tests the claim that 41 < µ2. Assume the samples are normally distributed, random and independent. of + o S1 = 0.55; s2 = 0.64 41.79 ; 2 = 42.01 n1 = 41 ; n2 = 36 Standard Error t-Test Statistic Degrees of Freedom (E – 22) – (41 – 2) Smaller of (n1 – 1) or (n2 – 1) t = - n2 a. Calculate the Standard Error si , = (use 3 decimal places) b. Calculate the t-test statistic using the standard error from part a. t= (use 2 decimal places) C. What are the degrees of freedom? d f = d. At a = 0.05. Use the distribution table to find the critical values for the rejection region te (use 4 decimal places)

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Tests the claim that u1 < µ2. Assume the samples are normally distributed, random and independent.
S1 = 0.55; s2 = 0.64
I1 = 41.79 ; I2 = 42.01
n1 = 41; n2 = 36
Standard Error
t-Test Statistic
Degrees of Freedom
(71 – 72) – (41 – 42) Smaller of (n1 – 1) or (n2 – 1)
t =
ni
n2
a. Calculate the Standard Error s-i, =
(use 3 decimal places)
b. Calculate the t-test statistic using the standard error from part a. t =
(use 2 decimal places)
c. What are the degrees of freedom? df =
d. At a = 0.05. Use the distribution table to find the critical values for the rejection region
t =
(use 4 decimal places)
Transcribed Image Text:Tests the claim that u1 < µ2. Assume the samples are normally distributed, random and independent. S1 = 0.55; s2 = 0.64 I1 = 41.79 ; I2 = 42.01 n1 = 41; n2 = 36 Standard Error t-Test Statistic Degrees of Freedom (71 – 72) – (41 – 42) Smaller of (n1 – 1) or (n2 – 1) t = ni n2 a. Calculate the Standard Error s-i, = (use 3 decimal places) b. Calculate the t-test statistic using the standard error from part a. t = (use 2 decimal places) c. What are the degrees of freedom? df = d. At a = 0.05. Use the distribution table to find the critical values for the rejection region t = (use 4 decimal places)
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A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups. The two groups may be related or unrelated. It allows us to compare the average values of the two data sets and determine if they came from the same population. 

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