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INTRODUCTION TO t-STATISTIC: hypothesis testing tool in which estimated…
INTRODUCTION TO t-STATISTIC: hypothesis testing tool in which estimated standard error is used in the z-score formula denominator; substitue for a z-score
ESTIMATED STANDARD ERROR OF M:
approximation of the standard distance between a sample mean and the population mean
DIFFERENCE BETWEEN t-FORMULA & z-SCORE FORMULA: the z-score uses the actual population variance, σ (or the standard deviation), and the t formula uses the corresponding sample variance (or standard deviation) when the population value is not known.
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SAMPLE SIZE/DEGREES OF FREEDOM:
as sample size increases, so does the value for degrees of freedom
t-DISTRIBUTION SHAPE:
more variable than the normal distribution as indicated by the flatter and more spread-out shape.
ASSUMPTIONS OF THE t-TEST: 1.The values in the sample must consist of independent observation. 2.The population sampled must be normal.
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PERCENTAGE OF VARIANCE ACCOUNTED FOR BY THE TREATMENT:
measurement of reduction in variability after removing the treatment effect
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FACTORS AFFECTING WIDTH OF CONFIDENCE INTERVAL:
To gain more confidence in your estimate, you must increase the width of the interval. Conversely, to have a smaller, more precise interval, you must give up confidence.
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