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Hypothesis Testing and Regression Analysis in ISDS, Exams of Nursing

A study guide or exam preparation material for a course in introductory statistics and decision sciences (isds). It covers key concepts and terminology related to hypothesis testing, including the null hypothesis, type i errors, test statistics, and p-values. It also delves into regression analysis, discussing topics such as the least squares method, residuals, r-squared, and multicollinearity. The document seems to be designed to help students review and solidify their understanding of these fundamental statistical techniques, which are widely used in various fields of study and research. By studying this material, students can gain a deeper grasp of the underlying principles and practical applications of hypothesis testing and regression analysis, equipping them with the necessary skills to tackle real-world data analysis challenges.

Typology: Exams

2023/2024

Available from 10/14/2024

Toperthetop
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Download Hypothesis Testing and Regression Analysis in ISDS and more Exams Nursing in PDF only on Docsity! ISDS Final Exam Null Hypothesis - correct answer ✔✔The accepted and assumed position in a hypothesis test is stated in the... Type 1 error - correct answer ✔✔When we reject a null hypothesis that is actually true, we have committed a Alternative - correct answer ✔✔The goal is to determine whether there is enough evidence to infer that the _________ hypothesis is true type 1 error - correct answer ✔✔The significance level is the probability of a Null hypothesis - correct answer ✔✔The equal sign is always placed in the Rejection Region - correct answer ✔✔The area beyond the critical value is the Test Statistic - correct answer ✔✔The p value is calculated using the... T statistic - correct answer ✔✔What is it called when we substitute the sample standard deviation "s" in place of the unknown population standard deviation? Broader and flatter - correct answer ✔✔The "t" distribution tends to be ____ than the "z" distribution for smaller sample sizes? - Consists of a fixed number "n" of trials - The outcome can be classified into one K categories called cells - The probability (p) for each outcome remains constant for each trial - Each trial of the experiment is independent of the other trials - correct answer ✔✔What are the characteristics of a multinomial experiment? Independent variable - correct answer ✔✔In regression analysis which variable is used to predict another variable_____ Least squares - correct answer ✔✔The method used to find the linear line that best fits the actual data is ____ Residuals - correct answer ✔✔The difference between the actual y values and the predicted y values is the The percentage of the dependent variable explained by the independent variables - correct answer ✔✔The "r" squared value gives us____ The slope is equal to 0 - correct answer ✔✔The null hypothesis used in simple regression states That we cannot reject the null hypothesis and that there is no relationship - correct answer ✔✔A p value for the coefficient in a simple regression is .15. What can we infer from this? Residual analysis - correct answer ✔✔To ensure the preconditions are met for a regression analysis, the best approach would be to perform a __________ F test - correct answer ✔✔The global test in multiple regression is done with the __________ multicollinearity - correct answer ✔✔The condition that exists when independent variables are correlated with one another is _________ Stepwise regression - correct answer ✔✔This brings independent variables into the equation one at a time ____________ Adjusted r squared - correct answer ✔✔This is a better statistic for determining how strong the relationships are in multiple regression because it accounts for the bias caused by multiple independent variables _____________