[1] Test using independent and dependent t-test. (Show complete steps). May encode or handwritten. (Choose one t-test that is fit for the problem. Refer to the photo below) The average amount of time boys and girls ages 7 through 11 spend playing sports each day is believed to be the same. An experiment is done; data is collected, resulting in the table below:   Sample Size Average No. of hours playing sports per day Sample Standard deviation Girls 9 2 hours 0.75 Boys 16 3.2 hours 1.00 Is there a difference in the average amount of time boys and girls ages 7 through 11 play sports each day? Test at a 5% level of significance

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[1] Test using independent and dependent t-test. (Show complete steps). May encode or handwritten. (Choose one t-test that is fit for the problem. Refer to the photo below)

The average amount of time boys and girls ages 7 through 11 spend playing sports each day is believed to be the same. An experiment is done; data is collected, resulting in the table below:

  Sample Size Average No. of hours playing sports per day Sample Standard deviation
Girls 9 2 hours 0.75
Boys 16 3.2 hours 1.00

Is there a difference in the average amount of time boys and girls ages 7 through 11 play sports each day? Test at a 5% level of significance.

INDEPENDENT / DEPENDENT T-TEST
T-TEST ONE SAMPLE MEAN
STEP 1: State the null and the alternative hypothesis.
STEP 2: Specify the level of significance. (use a = 1% = 0.01)
STEP 3: Determine the test static to be used and the degree of freedom (df).
STEP 4: Compute the value of the tcomputed.
tcomputed =
STEP 5: Make the decision.
Example:
The (tcomputed = -4.00|>|tcritical = ±2.947|
Since the |tcomputed| is greater than the |tcritical|, we shall reject the null
hypothesis (Ho) and accept the alternative hypothesis (Ha).
STEP 6: State the conclusion.
Example:
At 1% level of significance with df = 15, the arithmetic mean grade of 100
obtained by medical practitioners is not true.
T-TEST ONE SAMPLE MEAN (GOSETT T-TEST)
ž1-x2
t =
Ts1 (n1–1)]+[s2°(n2-1)]
[ni+n2] – 2
[무
STEP 1: State the null and the alternative hypothesis.
STEP 2: Specify the level of significance.
STEP 3: Determine the test static to be used and the degree of freedom (df).
STEP 4: Compute the value of the tcomputed.
ã1-x2
t =
[s1 (n1–1)]+[s2°(n2-1)]
[n1+n2] – 2
n1
STEP 5: Make the decision.
STEP 6: Draw a conclusion.
PAIRED T-TEST (DEPENDENT T-TEST)
STEP 1: State the null and the alternative hypotheses.
STEP 2: Specify the level of significance.
STEP 3: Determine the test static to be used and the degree of freedom (df).
STEP 4: Compute for t-static.
STEP 5: Make the decision.
STEP 6: Conclusion
Transcribed Image Text:INDEPENDENT / DEPENDENT T-TEST T-TEST ONE SAMPLE MEAN STEP 1: State the null and the alternative hypothesis. STEP 2: Specify the level of significance. (use a = 1% = 0.01) STEP 3: Determine the test static to be used and the degree of freedom (df). STEP 4: Compute the value of the tcomputed. tcomputed = STEP 5: Make the decision. Example: The (tcomputed = -4.00|>|tcritical = ±2.947| Since the |tcomputed| is greater than the |tcritical|, we shall reject the null hypothesis (Ho) and accept the alternative hypothesis (Ha). STEP 6: State the conclusion. Example: At 1% level of significance with df = 15, the arithmetic mean grade of 100 obtained by medical practitioners is not true. T-TEST ONE SAMPLE MEAN (GOSETT T-TEST) ž1-x2 t = Ts1 (n1–1)]+[s2°(n2-1)] [ni+n2] – 2 [무 STEP 1: State the null and the alternative hypothesis. STEP 2: Specify the level of significance. STEP 3: Determine the test static to be used and the degree of freedom (df). STEP 4: Compute the value of the tcomputed. ã1-x2 t = [s1 (n1–1)]+[s2°(n2-1)] [n1+n2] – 2 n1 STEP 5: Make the decision. STEP 6: Draw a conclusion. PAIRED T-TEST (DEPENDENT T-TEST) STEP 1: State the null and the alternative hypotheses. STEP 2: Specify the level of significance. STEP 3: Determine the test static to be used and the degree of freedom (df). STEP 4: Compute for t-static. STEP 5: Make the decision. STEP 6: Conclusion
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