Centering HLM offers the options to use predictors as they are‚ or to use them after grand- or group-mean centering them. The choice of centering method is dictated by the question studied‚ and great care should be taken to select a form of centering appropriate to the model considered‚ as the interpretation of coefficients in the model is dependent on the type of centering used. We start with an example where a simple linear transformation of a predictor is used to ensure that the interpretation
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know from the CLT that sample means are normally distributed around the real population mean (). Any time you have a sample mean within E (margin of error) of then the confidence interval will contain . Since 95% of the sample means are within E of then 95% of the confidence interval constructed in this way will contain. • Why do we use confidence intervals verses point estimates? The sample mean is a point estimate (single number estimate) of the population mean – Due to sampling error‚ we know
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known to have a skewed-right distribution with a mean of 10 minutes and a standard deviation of 8 minutes. Suppose 100 flights have been randomly sampled. Describe the sampling distribution of the mean waiting time between when the airplane taxis away from the terminal until the flight takes off for these 100 flights. a) Distribution is skewed-right with mean = 10 minutes and standard error = 0.8 minutes. b) Distribution is skewed-right with mean = 10 minutes and standard error = 8 minutes. c) Distribution
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best completes each statement or answers the question. A hypothesis test is to be performed. Determine the null and alternative hypotheses. 1) A manufacturer claims that the mean amount of juice in its 16 ounce bottles is 16.1 ounces. A consumer advocacy group wants to perform a hypothesis test to determine whether the mean amount is actually less than this. Classify the hypothesis test as two-tailed‚ left-tailed‚ or right-tailed. 2) At one school‚ the average amount of time that tenth-graders spend
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difference in the mean purchase for men customers versus women customers. It wishes to estimate this difference using a 95 percent confidence level. If the sample size is n = 10 from each population‚ the samples are independent‚ and sample standard deviations are used‚ and the variances are assumed equal‚ then the critical value will be t = 2.1009. Answer: TRUE Diff: 2 Keywords: confidence interval‚ mean difference‚ independent‚ sample Section: 10-1 Estimation for Two Population Means Using Independent
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NORMDIST formula was used to calculate: =NORMDIST(5.5‚1.88‚1.99‚True) X= 5.5 Mean= 1.88 Standard Deviation=1.19 b) 32 to 35 weeks = 43.83% The NORMDIST formula was used to calculate: =NORMDIST (5.5‚5.73‚1.48‚True) X= 5.5 Mean= 5.73 Standard Deviation=1.48 c) 37 to 39 weeks = 4.66% The NORMDIST formula was used to calculate: =NORMDIST(5.5‚7.33‚1.09‚ True) X= 5.5 Mean= 7.33 Standard Deviation=1.09 d) 42 weeks and over = 2.75% The NORMDIST
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WHAT NULL HYPOTHESIS ISTESTED BY ANOVA? ANALYSIS OF VARIANCE IS A STATISTICAL METHOD USED TO TEST DIFFERENCES BETWEEN TWO OR MORE MEANS. IT IS USED TO TEST GENERAL RATHER THAN SPECIFIC DIFFERENCES AMONG MEANS. THUS THE NULL HYPOTHESIS IS CALLED AN OMNIBUS NULL HYPOTHESIS IT MEANS THAT AT LEAST ONE POPULATION MEAN IS DIFFERENT FROM AT LEASTONE OTHER MEAN. THE ANOVA DOES NOT REVEAL WHICH PAIR IS SIGNIFICANT‚ THUS A FOLLOW UP TEST IS NECESSARY TO DETERMINEWHICH PAIR IS DIFFERENT FROM EACH
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is a ratio‚ numerical‚ discrete variable. Services is a ratio‚ numerical‚ discrete variable. Debit‚ interest and city are a categorical‚ nominal variable. As the graph‚ shows below‚ the balance of the typical customer‚ otherwise known as the mean is equal to 1499.87. 12 customers have more than $2‚000 in their account. This number is relatively high because the account balances tend to cluster between $1‚000 and $2‚250. The standard deviation of the checking account balances 596905 and
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reports that it has changed‚ even if it hasn’t. We can tell if the expectation has occurred when the descending mean is greater than the ascending mean. Habituation occurs when the participant hesitates too long to switch the response‚ responding with a Y or N‚ even after detection of the stimulus has changed. We can tell this is habituation if the ascending mean is greater than the descending mean. We conducted two total trials at each frequency (i.e.‚ 2 ascending trials and 2 descending trials) to get
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the sample mean and the sample standard deviation. What can he learn from this sample mean about the population mean? This is an important problem and is addressed by the Central Limit Theorem. For now‚ let us not bother about what this theorem states but we will look at how it could help us in answering our question. The Central Limit Theorem tells us that if we take very many samples the means of all these samples will lie in an interval around the population mean. Some sample means will be larger
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