Question 2: To estimate pi – P2, a 95% confidence interval is computed as (-0.13,0.32). Assuming all as- sumptions are met, what can be gleaned from this? (a) An error was made since proportions can't be negative. (b) It would appear that p1 # p2 since the differences can be non-zero. (c) We can't statistically say that pi + p2 since our confidence interval includes 0. (d) We would conclude HA : P1 # P2 at the a = 0.05 significance level.
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
Question 1 and question 2
![For each of the following, explain what is wrong and why.
(a) Az statistic is used to test the null hypothesis that P1 = P2.
(b) If two sample proportions are equal, then the sample counts are equal.
(c) When testing Ho: P1 = P2, we must expect at least 10 successes and failures in our random
samples.
(d) Does a higher proportion of second year students study 10 hours weekly than first year
students? To find out, I randomly choose a statistics course and then look at the proportion
of first year students in that class and of second year students in that class that study 10
hours per week.
Question 2:
To estimate p1 – p2, a 95% confidence interval is computed as (-0.13, 0.32). Assuming all as-
sumptions are met, what can be gleaned from this?
(a) An error was made since proportions can't be negative.
(b) It would appear that p1 + P2 since the differences can be non-zero.
(c) We can't statistically say that pi + p2 since our confidence interval includes 0.
(d) We would conclude HA : Pı # P2 at the a = 0.05 significance level.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff220b9e4-69ca-4350-a40f-3d35ad6543b0%2Fba4cc234-de16-44e6-887b-80fb7dcc864b%2Fhai2q9_processed.jpeg&w=3840&q=75)
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