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The authors of a paper studied a random sample of 347 Twitter users. For each Twitter user in the sample, the tweets sent during a particular time period were analyzed and the Twitter user was classified into one of the following categories based on the type of messages they usually sent. Category Description IS Information sharing Opinions and complaints RT Random thoughts ME Me now (what I am doing now) Other The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper). IS oc RT ME o Observed count 52 61 62 99 73 Twitter Type Carry out a hypothesis test to determine if there is convincing evidence that the proportions of Twitter users falling into each of the five categories are not all the same. Use a significance level of 0.05. (Hint: See Example 12.2.) Let P Pa. Py. P and ps be the proportions of Twitter users falling into the five categories. State the appropriate null and alternative hypotheses. O Hạ: P = P2 - P, " P." Ps" 0.5 H,: Ho is not true. O Ho: P1"P2" P3 = Pa = Ps = 347 H: Ho is not true. O Hại P " P2 = P3 - Pa" Ps" 0.05 H: Họ is not true. O Hoi Pq = P2 = P3 = P, = Ps = 0.2 H: Ho is not true. O Hạ: P = P2 = P3 = P4 = Ps = 70 H,i Ho is not true. Find the test statistic and P-value. (Use technology. Round your test statistic to three decimal places and your P-value to four decimal places.) p-value = State the conclusion in the problem context. O Do not reject H. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. O Reject Hg. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same.

The authors of a paper studied a random sample of 347 Twitter users. For each Twitter user in the sample, the tweets sent during a particular time period were analyzed and the Twitter user was classified into one of the following categories based on the type of messages they usually sent. Category Description IS Information sharing Opinions and complaints RT Random thoughts ME Me now (what I am doing now) Other The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper). IS oc RT ME o Observed count 52 61 62 99 73 Twitter Type Carry out a hypothesis test to determine if there is convincing evidence that the proportions of Twitter users falling into each of the five categories are not all the same. Use a significance level of 0.05. (Hint: See Example 12.2.) Let P Pa. Py. P and ps be the proportions of Twitter users falling into the five categories. State the appropriate null and alternative hypotheses. O Hạ: P = P2 - P, " P." Ps" 0.5 H,: Ho is not true. O Ho: P1"P2" P3 = Pa = Ps = 347 H: Ho is not true. O Hại P " P2 = P3 - Pa" Ps" 0.05 H: Họ is not true. O Hoi Pq = P2 = P3 = P, = Ps = 0.2 H: Ho is not true. O Hạ: P = P2 = P3 = P4 = Ps = 70 H,i Ho is not true. Find the test statistic and P-value. (Use technology. Round your test statistic to three decimal places and your P-value to four decimal places.) p-value = State the conclusion in the problem context. O Do not reject H. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. O Reject Hg. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The authors of a paper studied a random sample of 347 Twitter users. For each Twitter user in the sample, the tweets sent during a particular time period were analyzed and the Twitter user was classified into one of the following categories based on the type of messages they usually sent. Category Description IS Information sharing ос Opinions and complaints RT Random thoughts МЕ Me now (what I am doing now) Other The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper). Twitter Type oc RT IS МЕ Observed count 52 61 62 99 73 Carry out a hypothesis test to determine if there is convincing evidence that the proportions of Twitter users falling into each of the five categories are not all the same. Use a significance level of 0.05. (Hint: See Example 12.2.) Let p,, P2, P3 Pa, and p, be the proportions of Twitter users falling into the five categories. State the appropriate null and alternative hypotheses. O Ho: P1 = P2 = P3 = P4 = P5 = 0.5 H3: H, is not true. O Ho: P1 = P2 = P3 = P4 = Ps = 347 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = Ps = 0.05 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = P5 = 0.2 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = P5 = 70 H: H, is not true. Find the test statistic and P-value. (Use technology. Round your test statistic to three decimal places and your P-value to four decimal places.) x2 = P-value = State the conclusion in the problem context. O Do not reject H.. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. O Reject H,. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same.
Transcribed Image Text:The authors of a paper studied a random sample of 347 Twitter users. For each Twitter user in the sample, the tweets sent during a particular time period were analyzed and the Twitter user was classified into one of the following categories based on the type of messages they usually sent. Category Description IS Information sharing ос Opinions and complaints RT Random thoughts МЕ Me now (what I am doing now) Other The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper). Twitter Type oc RT IS МЕ Observed count 52 61 62 99 73 Carry out a hypothesis test to determine if there is convincing evidence that the proportions of Twitter users falling into each of the five categories are not all the same. Use a significance level of 0.05. (Hint: See Example 12.2.) Let p,, P2, P3 Pa, and p, be the proportions of Twitter users falling into the five categories. State the appropriate null and alternative hypotheses. O Ho: P1 = P2 = P3 = P4 = P5 = 0.5 H3: H, is not true. O Ho: P1 = P2 = P3 = P4 = Ps = 347 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = Ps = 0.05 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = P5 = 0.2 H: H, is not true. O Ho: P1 = P2 = P3 = P4 = P5 = 70 H: H, is not true. Find the test statistic and P-value. (Use technology. Round your test statistic to three decimal places and your P-value to four decimal places.) x2 = P-value = State the conclusion in the problem context. O Do not reject H.. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. O Reject H,. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same.
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