To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the three treatments. You are given the results below. Treatment Observation A 20 30 25 33 B 22 26 20 28 C 40 30 28 22 The test statistic to test the null hypothesis equals .

The test statistic to test the null hypothesis equals 1.059

Step-by-step explanation:

From the given information; we have:

Treatment               Observations

A                                20        30         25       33

B                                22         26        20       28

C                               40         30         28       22

The objective is to find the  test statistic to test the null hypothesis; in order to do that;we must first run through a series of some activities.

Let first compute the sum of the square;

Total sum of squares (TSS) = Treatment sum of squares  +    Error sum of squares   (ESS)

where:

(TSS) =  with (n-1)   df

    with (v-1)  df

  with (n-v) df

where;

v= 3

4

i = 1,2,3

n =12

is the observation for the treatment

is the mean of the   treatment  i = 1,2,3 ;  j = 1,2,3,4

  is the overall mean

From the given data

Total sum of squares (TSS) = Treatment sum of squares  +    Error sum of squares   (ESS)

(TSS) =  378 - 72

(TSS) =  306

Now; to the mean square between treatments (MSTR); we use the formula:

MSTR = TrSS/df(TrSS)

MSTR = 72/(3 - 1)

MSTR = 72/2

MSTR = 36

The mean square within treatments  (MSE) is:

MSE = ESS/df(ESS)

MSE = 306/(12-3)

MSE = 306/(9)

MSE = 34

The test statistic to test the null hypothesis is :

T = 1.059

42.4

step-by-step explanation:

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