LET'S SAY THESE ARE THE NUMBER OF STRIKE-OUTS A PITCHER THROWS IN THE NUMBER OF INNINGS PITCHED (WE HAVE 6 PAIRS OF DATA POINTS)

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LET’S SAY THESE ARE THE NUMBER OF STRIKE-OUTS A PITCHER
THROWS IN THE NUMBER OF INNINGS PITCHED (WE HAVE 6 PAIRS OF DATA POINTS) THE INNINGS PITCHED ARE THE ”X” VALUES (INDEPENDENT VARIABLE) AND THE STRIKE-OUTS ARE THE ”Y” VALUES (DEPENDENT VARIABLE) FOR EXAMPLE WHEN PITCHING 4 INNINGS, THE PITCHER STRUCK OUT 6 BATTERS (ETC.) X-VALUES ARE: 4, 3, 5, 11, 10, 14 THE CORRESPONDING ”Y” VALUES ARE: 6, 7, 12, 17, 10, 14
(a) CALCULATE THE SLOPE AND Y-INTERCEPT FOR EACH WHAT IS THE ACTUAL LINE EQUATION?
(b) CALCULATE THE CORRELATION COEFFICIENT “r” VALUE
(c) WOULD YOU SAY ( AND WHY) THE CORRELATION IS SIGNIFICANT
(d) WHAT DO THE LINE EQUATIONS INDICATE THE Y’-VALUE SHOULD BE FOR X = 18 INNINGS ?
(e) WHAT IS THE STANDARD ERROR OF THE ESTIMATE AND HOW MUCH OF VARIATION IN “Y” IS EXPLAINED BY THE VARIATION IN “X” ? HOW MUCH IS NOT EXPLAINED ?

 
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LET’S SAY THESE ARE THE NUMBER OF STRIKE-OUTS A PITCHER THROWS IN THE NUMBER OF INNINGS PITCHED (WE HAVE 6 PAIRS OF DATA POINTS)

/in /by

LET’S SAY THESE ARE THE NUMBER OF STRIKE-OUTS A PITCHER
THROWS IN THE NUMBER OF INNINGS PITCHED (WE HAVE 6 PAIRS OF DATA POINTS) THE INNINGS PITCHED ARE THE ”X” VALUES (INDEPENDENT VARIABLE) AND THE STRIKE-OUTS ARE THE ”Y” VALUES (DEPENDENT VARIABLE) FOR EXAMPLE WHEN PITCHING 4 INNINGS, THE PITCHER STRUCK OUT 6 BATTERS (ETC.) X-VALUES ARE: 4, 3, 5, 11, 10, 14 THE CORRESPONDING ”Y” VALUES ARE: 6, 7, 12, 17, 10, 14
(a) CALCULATE THE SLOPE AND Y-INTERCEPT FOR EACH WHAT IS THE ACTUAL LINE EQUATION?
(b) CALCULATE THE CORRELATION COEFFICIENT “r” VALUE
(c) WOULD YOU SAY ( AND WHY) THE CORRELATION IS SIGNIFICANT
(d) WHAT DO THE LINE EQUATIONS INDICATE THE Y’-VALUE SHOULD BE FOR X = 18 INNINGS ?
(e) WHAT IS THE STANDARD ERROR OF THE ESTIMATE AND HOW MUCH OF VARIATION IN “Y” IS EXPLAINED BY THE VARIATION IN “X” ? HOW MUCH IS NOT EXPLAINED ?

 
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A researcher claims the proportion of auto accidents that involve

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A researcher claims the proportion of auto accidents that involve
teenage drivers is greater than 10%. ABC Insurance Company checks police records on 200 randomly selected auto accidents and notes that teenagers were at the wheel in 25 of them. Assume the company wants to use a 0.10 significance level to test the researcher’s claim.
(a) What is the appropriate hypothesis test to use for this analysis(one-sample z-test for the population proportion, one-sample t-test for population proportion, one-sample z-test for population mean, or one-sample t- test for population mean?) Why?
(b) Identify the null hypothesis and the alternative hypothesis
(c) How do you determine the test statistic?
(d) How do you determine the P-value for this test?
(e) Compare p-value and significance level α. What decision should be made regarding the null hypothesis (e.g., reject or fail to reject) and why?
(f) Is there sufficient evidence to support the researcher’s claim that the proportion of auto accidents that involve teenage drivers is greater than 10%? How?

 
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Mimi was curious if regular excise really helps weight loss,

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Mimi was curious if regular excise really helps weight loss, hence
she decided to perform a hypothesis test. A random sample of 5 students was chosen. The students took a 30- minute exercise every day for 6 months. The weight was recorded for each individual before and after the exercise regimen. Does the data below suggest that the regular exercise helps weight loss? Assume Mimi wants to use a 0.05 significance level to test the claim.
Weight (pounds)
Subject Before After
1 190 180
2 170 160
3 185 190
4 160 160
5 200 190
(a) What is the appropriate hypothesis test to use for this analysis ( z-test for two proportions, t-test for two proportions, t-test for two dependent samples (matched pairs), or t-test for two independent samples) Why?
(b) Let μ1 = mean weight before the exercise regime. Let μ2 = mean weight after the exercise regime. Which of the following statements correctly defines the null hypothesis? (i) μ1 – μ2 > 0 (μd > 0)
(ii) μ1 – μ2 = 0 (μd = 0)
(iii) μ1 – μ2 < 0 (μd < 0)
(c) Let μ1 = mean weight before the exercise regime. Let μ2 = mean weight after the exercise regime. Which of the following statements correctly defines the alternative hypothesis?
(1) μ1 – μ2 > 0 (μd > 0)
(2) μ1 – μ2 = 0 (μd = 0)
(3) μ1 – μ2 < 0 (μd < 0)
(d) How would you determine the test statistic.
(e) How would you determine the p-value?
(f) Compare p-value and significance level α. What decision should be made regarding the null hypothesis (e.g., reject or fail to reject) and why?
(g) Is there sufficient evidence to support the claim that regular exercise helps weight loss?Why?

 
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