Term
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Definition
xbar - mew/(s/n^0.5)
where s = sample standard deviation |
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Term
| The t-statistic represents |
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Definition
| The number of sample standard errors xbar is from the population mean mew |
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Term
| 1. Properties of the t-distribution |
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Definition
| The t-distribution is different for different degrees of freedom |
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Term
| 2. Properties of the t-distribution |
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Definition
| The t-distribution is centered at 0 and is symmetric about 0 |
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Term
| 3. Properties of the t-distribution |
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Definition
| The area under the curve is 1. The area on either side of 0 equals 1/2 |
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Term
| 4. Properties of the t-distribution |
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Definition
| As t increases/decreases without bound, the graph approaches but never equals 0 |
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Term
| 5. Properties of the t-distribution |
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Definition
| The area in the tails of the t-distribution is a little greater than the area in the tails of the standard normal distribution |
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Term
| 6. Properties of the t-distribution |
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Definition
| As the sample size n increases, the density curve of t gets closer to the standard normal density curve |
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Term
| The differences between constructing CI from a population with an unknown mean mew and unknown sd sigma |
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Definition
1. s in place of sigma
2. t in place of z |
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Term
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Definition
| xbar - t(alpha/2)x(s/n^0.5) |
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Term
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Definition
| xbar + t(alpha/2)x(s/n^0.5) |
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Term
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Definition
| Do not require normality and the methods are resistant to outliers |
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