Facts About the Chi-Square Distribution Quiz

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: • The curve is nonsymmetrical and skewed to the right.

PDF page 598: • When df > 90, the chi-square curve approximates the normal distribution. For X ~

PDF page 598: • The mean, μ, is located just to the right of the peak.

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true:

PDF page 598: and the standard deviation, σ =

PDF page 598: = 44.7. Therefore, X ~ N(1,000, 44.7), approximately.

PDF page 598: = 44.7. Therefore, X ~ N(1,000, 44.7), approximately.

PDF page 598: where df = degrees of freedom, which depends on how chi-square is being used. If you want to practice calculating chisquare probabilities then use df = n – –1. The degrees of freedom for the three major uses are calculated differently. 2 For the χ distribution, the population mean is μ = df, and the population standard deviation is . 2 The random variable is shown as χ , but it may be any uppercase letter. The random variable for a chi-square distribution with k degrees of freedom is the sum of k independent, squared standard normal variables is 2 2 2 2 χ = (Z1) + (Z2) + ... + (Zk) , where the following are true: