The table below summarizes data from a survey of a sample of women. Using a 0.01 significance level, and assuming that the sample sizes of 800 men and 300 women are predetermined, test the claim that the proportions of agree/disagree responses are the same for subjects interviewed by men and the subjects interviewed by women. Does it appear that the gender of the interviewer affected the responses of women? Gender of Interviewer Woman 254 Man Women who agree Women who disagree 470 330 46 Click here to view the chi-square distribution table. Identify the null and alternative hypotheses. Choose the correct answer below. OA Ho: The proportions of agree/disagree responses are the same for the subjects interviewed by men and the subjects interviewed by women. H: The proportions are different. O B. Ho: The proportions of agree/disagree responses are different for the subjects interviewed by men and the subjects interviewed by women. H,: The proportions are the same. OC. Ho: The response of the subject and the gendar of the subject are independent. H4: The response of the subject and the gender of the subject are dependent. Compute the test statistic. (Round to three decimal places as needed.) Find the critical value(s).
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 and chi-square table.
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