Unit 5 Assignment 1: Homework Short Answer 1-7 p.158 1) Explain what is meant by the term “conditionally executed”. Conditionally executed is called a single alternative decision structure because it provides only one alternative path of execution. The action is conditionally executed because it is performed only when a certain condition is true. 2) You need to test a condition and then execute one set of statements if the condition is true. If the condition is false, you need to execute a different set of statements.
Rs = (.90)(.95) Reliability = 85.5% b. Explain how the configurations of the proposed designs differ. The proposed design differs because it has parallel components. This means if one of the parallel components fail its counterpart can keep the process going. This means that in order for the process to fail both components have to fail which makes the process more reliable.
Choose one answer. A. 0.26 pu B. 0.25 pu C. 0.3 pu Correct, well done! D. 0.24 pu This relay TMS is often only wrongly calculated if errors were made on the settings of the other downstream relays.
This will report any margin of error within individual testing due to imperfect reliability. The SEM is representing the true score within a range of scores. For example, an SEM of 3 is an indication that the true score is within a variable of 3 somewhere in either direction, plus or minus. The smaller the SEM reveals the
What is the dependent variable? a) sales managers b) amount of sales dollars c) salesperson d) number of contacts Download now QNT 561 Entire Course 5. Which of the following is most appropriately displayed with a frequency table? a) What percentage of people prefer Hunt's brand ketchup b) The home location of the most valuable customers c) How much explanatory value comes from the study's variables d) The relationship between gender and job performance 6. The manager of Paul's fruit and vegetable store is considering the purchase of a new seedless watermelon from a wholesale distributor.
3. The level of significance is the risk we assume of rejecting the null hypothesis when it is actually true. 4. Type II error is the probability or risk assumed by rejecting null hypothesis when it is actually true. 5.
What is the dependent variable? a) sales managers b) amount of sales dollars c) salesperson d) number of contacts QNT 561 Final Exam Solution QNT 561 Final Exam (Latest) 5. Which of the following is most appropriately displayed with a frequency table? a) What percentage of people prefer Hunt's brand ketchup b) The home location of the most valuable customers c) How much explanatory value comes from the study's variables d) The relationship between gender and job performance Answers To QNT 561 Final Exam Free Essays QNT 561 Final Exam (Latest) 6. The manager of Paul's fruit and vegetable store is considering the purchase of a new seedless watermelon from a wholesale distributor.
is biased, so we could make incorrect conclusions about model fit Detecting Heteroskedasticity: 1. Plot the regression residuals/errors, the “ehats,” or the squared residuals, the "ehats-squared", against the X variables (you should plot the residuals against each X variable separately to check which of the X variables might be a source of Heteroskedasticity). a. If Heteroskedasticity is not present, the variation in the ehats around (above and below) zero will be the same for all values of X. Figures 1a and 1b below are examples of residual plots when Heteroskedasticity is NOT present.
Any time an arguer intentionally leaves a premise or conclusion unstated, it is safe to assume that the omission was intended to conceal a weak or questionable step in the argument. Answer: false Reason: just sometime the missing statement is something so obvious and familiar that it would be tedious to state it explicitly. 4. When an argument is standardized, the conclusion is placed above the premises. Answer: false Reason: When an argument is standardized, the conclusion is placed under the premises.
Dimensionally all regions become sparse in density model. The sparsity behavior in high dimensionality makes all points look very similar to one another and the observation is true and these outliers may be discovered by examining the distribution of the data in a lower dimensional local subspace [2].Low dimensional subspace contains outlier and the character is latent to analysis. This is the combinational process of clustering and regression. To show the outlier pattern analysis and subspace analysis high dimensional model is determined. This can be a huge challenge to compute the high dimensional data because the simultaneous discovery of relevant data localities and subspaces is very difficult [2].High-dimensional methods provide an interesting direction for intentional understanding of outlier analysis when the subspaces are described in terms of the original attributes