check the null hypothesis that the mean is extra than or identical to 50. Use a one tail and a importance level of .05. A sample of 25 answers has an average=forty five and a variance=25.

erwachsenc6 2022-10-23 Answered
check the null hypothesis that the mean is extra than or identical to 50. Use a one tail and a importance level of .05.
A sample of 25 answers has an average=forty five and a variance=25.
You can still ask an expert for help

Expert Community at Your Service

  • Live experts 24/7
  • Questions are typically answered in as fast as 30 minutes
  • Personalized clear answers
Learn more

Solve your problem for the price of one coffee

  • Available 24/7
  • Math expert for every subject
  • Pay only if we can solve it
Ask Question

Answers (1)

Martha Dickson
Answered 2022-10-24 Author has 20 answers
You can use the t-test to test
H 0 : μ = 50
against
H A : μ > 50
The t statistics is obtained by
t e v a l = x ¯ μ 0 s / n
in which μ 0 is the mean under the hypothesis H 0 and s is the standard deviation of the sample.
We must compare t c a l with the critical value t 1 α , n 1 = 0.8242
Clearly, we don't reject H 0
Did you like this example?
Subscribe for all access

Expert Community at Your Service

  • Live experts 24/7
  • Questions are typically answered in as fast as 30 minutes
  • Personalized clear answers
Learn more

You might be interested in

asked 2022-06-13
A teacher wants to know if more than 15% of her students use online resources to complete their homework assignments instead of doing the homework independently. The teacher would like to carry out a test at the 0.05 significance level of
H 0 : p = 0.40
H a : p > 0.40
where p = the true proportion of students that use online resources to complete their homework assignments. One day after school, the teacher asked the 40 students studying in her classroom if they used online resources to complete their homework assignments or if they did their homework independently. Are the conditions to perform the significance test met?
No, the students do not represent a random sample and the Large Counts condition is not satisfied.
No, the students do not represent a random sample even though the Large Counts condition is satisfied.
No, the students represent a random sample, but the Large Counts condition is not satisfied.
Yes, the students represent a random sample and satisfy the Large Counts condition.
asked 2022-06-26
I am doing a two sample hypothesis problem that goes like this:
Research has shown that good hip range of motion and strength in throwing athletes results in improved performance and decreased body stress. The article “Functional Hip Characteristics of Baseball Pitchers and Position Players” (Am. J. Sport. Med., 2010: 383–388) reported on a study involving samples of 40 professional pitchers and 40 professional position players. For the pitchers, the sample mean trail leg total arc of motion (degrees) was 75.6 with a sample standard deviation of 5.9, whereas the sample mean and sample standard deviation for position players were 79.6 and 7.6, respectively. Assuming normality, test appropriate hypotheses to decide whether true average range of motion for the pitchers is less than that for the position players (as hypothesized by the investigators).
Using the information from the question I was able to get a t value of −2.63, from what I understand from here I'm supposed to compare this -2.63 to a critical value I get from the t table, or I can get find the p-value (I got 0.0043 from the normal table) and compare it to alpha which is the significance level. For both of these I don't really understand on which situations I'm supposed to be using for which method, It would be great if someone could explain this to me too. But regardless the main issue I have is that both of these requires a significance level to figure out, which wasn't given to me. Since I didn't know how to proceed I went to look at the answer to this question, which said this:
Because the one-tailed P-value is .005<.01, conclude at the .01 level that the difference is as stated.
The alternative hypothesis was chosen because the P value was lower than the significance level of .01 but if they had just chosen a smaller significance level(e.g. 0.001), then the alternative hypothesis would have been rejected
>So here my question is how did they know that a significance level of .01 was the level they are supposed to compare to?
Did they just choose it because there was no significance level given in the question?
asked 2022-06-01
Z-Test
μ < 40 z = 2.105263158 p = .017634141 x ¯ = 38 n = 100
(c) Based on your selection from part (b), what is the value of the standardized test statistic for this significance test?
(d) Based on your selection from part (b), what is the P-value for this significance test?
(e) What is the correct decision for this test, using a 0.05 level of signifcance?
A) Reject the null hypothesis
B) Do not reject the null hypothesis
asked 2021-01-27
Critical Thinking: One-Tailed versus Two-Tailed Tests For the same data and null hypothesis, is the P-value of a one-tailed test (right or left) larger or smaller than that of a two-tailed test? Explain.
asked 2022-05-07
Is Edwin Jaynes correct about statistics?
I've recently been reading Edwin Jaynes's book, Probability Theory: The Logic of Science, and I was struck by Jaynes's hostile view of what he dubs "orthodox statistics." He repeatedly claims that much of statistics is a giant mess, and argues that many commonplace statistical techniques are ad hoc devices which lack a strong theoretical footing. He blames historical giants like Karl Pearson and Ronald Fisher for the field's sorry state, and champions Bayesian methods as a healthier alternative.
From my personal perspective, his arguments make a lot of sense. However, there are a number of factors that prevent me from taking his criticism of statistics at face value. Despite the book's being published in 2003, the majority of its contents were written in the mid 20th century, making it a little dated. The field of statistics is reasonably young, and I'm willing to bet it's changed significantly since he levied his critiques.
Furthermore, I'm skeptical of how he paints statistics as having these giant methodological rifts between "frequentists" and "Bayesians." From my experience with other fields, serious methodological disagreement between professionals is almost nonexistent, and where it does exist it is often exaggerated. I'm also always skeptical of anyone who asserts that an entire field is corrupt--scientists and mathematicians are pretty intelligent people, and it's hard to believe that they were as clueless during Jaynes's lifetime as he claims.
Questions:
1. Can anyone tell me if Jaynes's criticisms of statistics were valid in the mid 20th century, and furthermore whether they are applicable to statistics in the present day? For example, do serious statisticians still refuse to assign probabilities to different hypotheses, merely because those probabilities don't correspond to any actual "frequencies?"
2. Are "frequentists" and "Bayesians" actual factions with strong disagreements about statistics, or is the conflict exaggerated?
asked 2022-06-16
To test for the significance of the phi correlation, one must use the ______________ distribution.
Group of answer choices:
1.t
2. Chi-square
3. z
4. F
asked 2021-01-10
A company is marketing a new product they say works better than the traditional test tube. There is so much interest in the product that 30 different labs around the world are testing the claim that this product is actually better. If each study uses an alpha level (alpha) of .10, and if the null hypothesis is true (that the test tube isn't any better that the traditional one), how many of the hypothesis tests would we expect to incorrectly find statistical significance (that is, conclude that the new test tube is better, when it actually isn't)?

New questions