Qmb6358 - Study guides, Class notes & Summaries

Populationthe whole that we are interested in Samplea part for which we have data ParameterA numerical summary from a population StatisticA numerical summary from a sample IdentifiersOnly purpose is to give more information about the case ex. Real Estate - Parcel Number Categorical DataWhen data is put into groups. Ex. Area of town We usually talk about percentages and/or proportions

Goodness-of-Fit Measures We will introduce three measures to judge how well the sample regression fits the data. 1. The Standard Error of the Residual (Estimate). 2. The Coefficient of Determination (R^2) 3. The Adjusted R^2 Mean Squared Error To compute the standard error of the residual, we first compute the mean squared error. - we first compute the error sum of squares - dividing SSE by the appropriate degrees of freedom, n-k-1, yields the mean squared error, MSE

Data was collected from a random selection of students at UF. One of the questions asked how many hours they had slept the previous night. The 90% confidence interval comparing underclassmen to upperclassmen was (0.015, 0.9153) . What is the conclusion statement? We are 95% confident that the population mean hours of sleep for underclassmen is between 0.015 more to 0.9153 more than that of upperclassmen. In a two sample t confidence interval, you are estimating: a. the two individual ...

Populationthe whole that we are interested in Samplea part for which we have data ParameterA numerical summary from a population StatisticA numerical summary from a sample IdentifiersOnly purpose is to give more information about the case ex. Real Estate - Parcel Number Categorical DataWhen data is put into groups. Ex. Area of town We usually talk about percentages and/or proportions OrdinalIf Categories have an intrinsic order.

Goodness-of-Fit Measures We will introduce three measures to judge how well the sample regression fits the data. 1. The Standard Error of the Residual (Estimate). 2. The Coefficient of Determination (R^2) 3. The Adjusted R^2 Mean Squared Error To compute the standard error of the residual, we first compute the mean squared error. - we first compute the error sum of squares - dividing SSE by the appropriate degrees of freedom, n-k-1, yields the mean squared error, MSE

Data was collected from a random selection of students at UF. One of the questions asked how many hours they had slept the previous night. The 90% confidence interval comparing underclassmen to upperclassmen was (0.015, 0.9153) . What is the conclusion statement? We are 95% confident that the population mean hours of sleep for underclassmen is between 0.015 more to 0.9153 more than that of upperclassmen. In a two sample t confidence interval, you are estimating: a. the two individual ...