A jar of peanuts is supposed to have 24 ounces of peanuts. The filling machine inevitably experiences fluctuations in filling, so a quality-control manager randomly samples 12 jars of peanuts from the storage facility and measures their contents. She obtains the accompanying data. Complete parts (a) through (d) below. Click here to view the peanut jar data. Click here to view the table of critical values of the chi-square distribution. Click here to view the standard normal distribution table (page 1). Click here to view the standard normal distribution table (page 2). Peanut jar data V Yes 23.94 23.75 24.19 23.28 23.85 23.82 No 23.49 24.14 23.76 23.52 24.31 24.61 (b) Determine the sample standard deviation. Print Done s = 0.377 (Round to three decimal places as needed.) (c) Construct a 90% confidence interval for the population standard deviation of the number of ounces of peanuts. Select the correct choice below and fill in the answer boxes to complete your choice. (Use ascending order. Round to three decimal places as needed.) O A. There is 90% confidence that the population standard deviation is between and B. There is a 90% chance that the true population standard deviation is between and O C. If repeated samples are taken, 90% of them will have the sample standard deviation between and
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.
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