section 7.1 hypothesis testing: hypothesis: null hypothesis (h 0 ): alternative hypothesis (h 1 ): a...

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Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing hypotheses should be believed (analogous to a court trial) a statement often involving the value of a parameter in a distribution that we want to decide whether or not to believe; the hypothesis is called simple if it specifies only one possible value and is called composite if it specifies multiple possible values a statement assumed to be true at the outset of a hypothesis test (comparable to “innocence” in a court trial) a statement for which sufficient evidence is required before it will be believed (comparable to “guilt” in a court trial)

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Page 1: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

Section 7.1Hypothesis Testing:

Hypothesis:

Null Hypothesis (H0):

AlternativeHypothesis (H1):

a statistical analysis used to decide which of two competing hypotheses should be believed (analogous to a court trial)

a statement often involving the value of a parameter in a distribution that we want to decide whether or not to believe; the hypothesis is called simple if it specifies only one possible value and is called composite if it specifies multiple possible values

a statement assumed to be true at the outset of a hypothesis test (comparable to “innocence” in a court trial)

a statement for which sufficient evidence is required before it will be believed (comparable to “guilt” in a court trial)

Page 2: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

Critical (Rejection)Region:

Type I Error:

Type II Error:

p-value(probability value):

a set describing the observed results of data collection that will lead to rejecting H0

rejecting H0 and accepting H1 when H0 is true (in a court trial, saying that the defendant is guilty when the defendant is really innocent)

failing to reject H0 when H1 is true (in a court trial, saying that the defendant is innocent when the defendant is really guilty)

denotes the probability of making a Type I error and is called the significance level of the test

denotes the probability of making a Type II error

the probability of observing data as supportive or more supportive of H1 than the actual data, calculated by assuming H0 is true

Page 3: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

Tables 7.1-1 and 7.1-2 summarize hypothesis tests about one or two proportions (for sufficiently large sample size(s)).

1. Do Text Exercise 7.1-2 three different ways:

First Way

(a) Let C0 = {x | x 0} be the critical region.

(b) = P{x : x 0; p = 3/5} =

P{X = 0; p = 3/5} =

(2/5)4 = 16/625 = 0.0256

= P{x : x > 0; p = 2/5} = P{X > 0; p = 2/5} =

1 – (3/5)4 = 1 – 81/625 =1 – P{X = 0; p = 2/5} =

544/625 = 0.8704

Page 4: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

Second Way

(a) Let C1 = {x | x 1} be the critical region.

(b) = P{x : x 1; p = 3/5} =

P{X = 0; p = 3/5} + P{X = 1; p = 3/5} =

(2/5)4 + (4)(3/5)(2/5)3 = 16/625 + 96/625 = 0.1792

= P{x : x > 1; p = 2/5} = P{X > 1; p = 2/5} =

1 – [(3/5)4 + (4)(2/5)(3/5)3] = 1 – 297/625 =

1 – [P{X = 0; p = 2/5} + P{X = 1; p = 2/5}] =

328/625 = 0.5248

Page 5: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

1.-continued

Third Way

(a) Let C2 = {x | x 2} be the critical region.

(b) = P{x : x 2; p = 3/5} =

P{X = 0; p = 3/5} + P{X = 1; p = 3/5} + P{X = 2; p = 3/5} =

(2/5)4 + (4)(3/5)(2/5)3 + (6)(3/5)2(2/5)2 = 16/625 + 96/625 + 216/625 =

= P{x : x > 2; p = 2/5} = P{X > 2; p = 2/5} =

(4)(2/5)3(3/5) + (2/5)4 = 96/625 + 16/625 = 0.1792

P{X = 3; p = 2/5} + P{X = 4; p = 2/5} =

328/625 = 0.5248

Page 6: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

2.

(a)

A bowl contains 2 red balls and 3 other balls each of which is either red or white. Let p denote the probability of drawing at random a red ball from the bowl. Consider testing H0: p = 2/5 vs. H1: p > 2/5. Drawing ten balls from the bowl one at a time at random and with replacement, we let X equal the number of red balls drawn, and we define the critical region to be C = {x | x 6}.

Calculate . = P{x : x 6; p = 2/5} =

P{X 6; p = 2/5} =

1 – P{X 5; p = 2/5} = 1 – 0.8338 = 0.1662(from Table II in Appendix B)

Page 7: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

2.-continued

(b) Calculate if p = 3/5.

If p = 3/5, = P{x : x 5; p = 3/5} =

P{X 5; p = 3/5} =

P{10 – X 5; 1 – p = 2/5} =

1 – P{10 – X 4; 1– p = 2/5} =

1 – 0.6331 = 0.3669 (from Table II in Appendix B)

Page 8: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

(c)

(d)

Calculate if p = 4/5.

Calculate if p = 1.

If p = 4/5, = P{x : x 5; p = 4/5} =

P{X 5; p = 4/5} =

P{10 – X 5; 1 – p = 1/5} = 1 – P{10 – X 4; 1– p = 1/5} =1 – 0.9672 = 0.0328 (from Table II in Appendix B)

If p = 1, = P{x : x 5; p = 1} =

0

Page 9: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

3. Do Text Exercise 7.1-6 and calculate if p = 0.15.

(a)

(b)

Let Y = the number of ones (1s) observed in 8000 rolls

The test statistic is z =

The one-sided critical region with = 0.05 is

y / 8000 – 1/6———————— (1/6)(5/6) / 8000

z z0.95 = – z0.05 = – 1.645

With y = 1265, we have z =1265 / 8000 – 1/6———————— = (1/6)(5/6) / 8000

– 2.05

Since z = – 2.05 < – z0.05 = – 1.645, we reject H0. We conclude that the probability of rolling a one (1) is less than 1/6.

Page 10: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

Since H0 is rejected. we expect the hypothesized proportion 1/6 not to be in the confidence interval:

1265 / 8000 1.960 (1265 / 8000)(6735 / 8000) / 8000

0.15013 , 0.16612

(c)

If p = 0.15, = P{z : z – 1.645; p = 0.15} = y / 8000 – 1/6

P ———————— – 1.645 ; p = 0.15 = (1/6)(5/6) / 8000 y / 8000 – 0.15 + (0.15 – 1/6)P ———————————— – 1.645 ; p = 0.15 =

(1/6)(5/6) / 8000

Find a two-sided 95% confidence interval, instead of the one-sided interval.

Page 11: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

y / 8000 – 0.15 1/6 – 0.15 P ———————— ———————— – 1.645 ; p = 0.15 = (1/6)(5/6) / 8000 (1/6)(5/6) / 8000

y / 8000 – 0.15 + (0.15 – 1/6)P ———————————— – 1.645 ; p = 0.15 =

(1/6)(5/6) / 8000

y / 8000 – 0.15 1/6 – 0.15 P ———————— ———————— – 1.7169 ; p = 0.15 = (0.15)(0.85) / 8000 (0.15)(0.85) / 8000

P(Z 2.46) = 1 – (2.46) =

1 – 0.9931 = 0.0069

Page 12: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

4. Do Text Exercise 7.1-16.

(a)

(b)

(c)

Let Y = number of yellow candies observed in n random candies

The test statistic is z =

The two-sided critical region with = 0.05 is

p – 0.2—————— (0.2)(0.8) / n

|z| 1.960

H0 is rejected when p = 5/54, but H0 is not rejected for each of the other 19 samples.

If H0 is true, then when this hypothesis test is performed repeatedly, H0 will be rejected 5% of the time in the long run.

Page 13: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

(d)

(e)

If 95% confidence intervals for p are repeatedly obtained, then 95% of the intervals in the long run will contain p.

If the 20 samples are pooled, then, p = 219——1124

We have z = 219 / 1124 – 0.2———————— = (0.2)(0.8) / 1124

– 0.43

Since z = – 0.43, and |z| < z0.025 = 1.960, we fail to reject H0. We conclude that the proportion of yellow candies produced is not different from 0.2.

Page 14: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

5. Do Text Exercise 7.1-20.

(a)

(b)

The test statistic is z =

The one-sided critical region with = 0.05 is

p1 – p2————————— p(1 – p)(1/n1 + 1/n2)

z 1.645

p1 = p2 =

p =

135 / 900 = 0.15 77 / 700 = 0.11

212 / 1600 = 0.1325

z = + 2.341

Since z = 2.341, and z z0.05 = 1.645, we reject H0. We conclude that the proportion of babies with low birth weight is higher for developing countries in Africa than for developing countries in the Americas.

Page 15: Section 7.1 Hypothesis Testing: Hypothesis: Null Hypothesis (H 0 ): Alternative Hypothesis (H 1 ): a statistical analysis used to decide which of two competing

(c)

(d)

The one-sided critical region with = 0.01 is z 2.326.

Since z = 2.341 z0.01 = 2.326, we would still reject H0.

The p-value of the test is

p1 – p2————————— p(1 – p)(1/n1 + 1/n2)

P 2.341 ; p1 = p2 =

P(Z 2.341) = 1 – (2.341) =1 – 0.9904 = 0.0096