**Text from the Image:** "Because 25 percent of the students in my morning statistics class watch eight or more hours of television a week, I conclude that 25 percent of all students at the university watch eight or more hours of television a week. The most important logical weakness of this conclusion would be: Multiple Choice - relying on a sample instead of surveying every student. - using a sample that may not be representative of all students. - failing to correct for unconscious interviewer bias. - assuming cause and effect where none exists." **Explanation:** This text presents a question about logical reasoning and statistical sampling. It describes a scenario where a conclusion is drawn about all university students based on a sample from a single statistics class. The question asks which statement represents the logical flaw in this conclusion. The focus is on understanding the representativeness and sampling errors involved when extending findings from a specific group to a larger population. There are no graphs or diagrams associated with this text.
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 attached
Given information-
Sample proportion, p = 0.25
We know that, sample is best estimator of population parameter when the sample is taken randomly and it is unbiased.
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