The authors of a paper studied a random sample of 350 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
OC Opinions and complaints
RT Random thoughts
ME Me now (what I am doing now)
O Other

The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper).

Twitter Type IS OC RT ME O
Observed count 50 61 64 102 73

Required:
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.

Some boys and girls were asked if they had a pet. one third of the group were boys. there were 20 boys. 20% of the girls had a pet. boys with a pet : girls with a pet = 1 : 5 i need to know how many girls there are.

Ialready asked this but i never got an answer. will give a high rating and perhaps brainliest. choose the linear inequality that describes the graph. the gray area represents the shaded region. y ≤ –4x – 2 y > –4x – 2 y ≥ –4x – 2 y < 4x – 2

Amachine that produces a special type of transistor (a component of computers) has a 2% defective rate. the production is considered a random process where each transistor is independent of the others. (a) what is the probability that the 10th transistor produced is the first with a defect? (b) what is the probability that the machine produces no defective transistors in a batch of 100? (c) on average, how many transistors would you expect to be produced before the first with a defect? what is the standard deviation? (d) another machine that also produces transistors has a 5% defective rate where each transistor is produced independent of the others. on average how many transistors would you expect to be produced with this machine before the first with a defect? what is the standard deviation? (e) based on your answers to parts (c) and (d), how does increasing the probability of an event a↵ect the mean and standard deviation of the wait time until success?