JMP output appears below for simple linear regression with data from the price, y (in $1000), of n = 28 Seattle home prices. The explanatory variable is the total number of square feet in the home. - Response Price ($000) Regression Plot 600 500 400 300 200 - Distributions 1000 1500 2000 2500 3000 3500 Square Feet Square Feet Summary of Fit RSquare RSquare Adi Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.560503 0.543599 356.8214 28 Analysis of Variance Sum of 1000 1500 2000 2500 3000 3500 Source DF F Ratio Squares Mean Square 1 249200.64 Model 249201 33.1585 - Summary Statistics Error 26 Prob > F C. Total 27 <.0001 Mean 1923.1071 Std Dev 653.11574 v Parameter Estimates Std Er Mean 123.42727 Term Estimate Std Error t Ratio Prob>lt Upper 95% Mean 2176.359 Lower 95% Mean 1669.8553 Intercept Square Feet 0.1470966 0.025545 73.938964 51.78554 1.43 0.1653 5.76 <.0001 28 (ooos) eoad
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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Question: Fill in a blank ANOVA table.
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