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Lisa [10]
3 years ago
8

What is the probability of getting more than 60 heads in 100 tosses?

Mathematics
2 answers:
solniwko [45]3 years ago
5 0
On a coin there is 2 sides so there is an even chance so if it’s 50 / 50 you would have to do more than 100 tosses to get over 60 heads
barxatty [35]3 years ago
3 0
100 coin tosses form a binomial distribution with number of trials = 100 and probability of success = 0.5

The probability of getting more than 60 heads in 100 tosses is P(X > 60), which can be evaluated by summing up the individual probabilities for X = 61 to 100. This gives 0.0176 or 1.76%.


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A study by the National Athletic Trainers Association surveyed random samples of 1679 high school freshmen and 1366 high school
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We conclude that there is no significant difference in the proportion of all Illinois high school freshmen and seniors who have used anabolic steroids.

Step-by-step explanation:

We are given that a study by the National Athletic Trainers Association surveyed random samples of 1679 high school freshmen and 1366 high school seniors in Illinois.

Results showed that 34 of the freshmen and 24 of the seniors had used anabolic steroids.

Let p_1 = <u><em>proportion of Illinois high school freshmen who have used anabolic steroids.</em></u>

p_2 = <u><em>proportion of Illinois high school seniors who have used anabolic steroids.</em></u>

SO, Null Hypothesis, H_0 : p_1=p_2      {means that there is no significant difference in the proportion of all Illinois high school freshmen and seniors who have used anabolic steroids}

Alternate Hypothesis, H_A : p_1\neq p_2      {means that there is a significant difference in the proportion of all Illinois high school freshmen and seniors who have used anabolic steroids}

The test statistics that would be used here <u>Two-sample z test for</u> <u>proportions</u>;

                        T.S. =  \frac{(\hat p_1-\hat p_2)-(p_1-p_2)}{\sqrt{\frac{\hat p_1(1-\hat p_1)}{n_1}+\frac{\hat p_2(1-\hat p_2)}{n_2} } }  ~ N(0,1)

where, \hat p_1 = sample proportion of high school freshmen who have used anabolic steroids = \frac{34}{1679} = 0.0203

\hat p_2 = sample proportion of high school seniors who have used anabolic steroids = \frac{24}{1366} = 0.0176

n_1 = sample of high school freshmen = 1679

n_2 = sample of high school seniors = 1366

So, <u><em>the test statistics</em></u>  =  \frac{(0.0203-0.0176)-(0)}{\sqrt{\frac{0.0203(1-0.0203)}{1679}+\frac{0.0176(1-0.0176)}{1366} } }

                                     =  0.545

The value of z test statistics is 0.545.

Since, in the question we are not given with the level of significance so we assume it to be 5%. <u>Now, at 5% significance level the z table gives critical values of -1.96 and 1.96 for two-tailed test.</u>

Since our test statistic lies within the range of critical values of z, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which <u>we fail to reject our null hypothesis</u>.

Therefore, we conclude that there is no significant difference in the proportion of all Illinois high school freshmen and seniors who have used anabolic steroids.

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3 years ago
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