Define the following:. 1. Leniency Error 2. Central Tendency Error 3. Strictness Error 4. Halo Error 5. Proximity Error 6. Contrast Error 7. Recency Effect
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Define the following:.
1. Leniency Error
2. Central Tendency Error
3. Strictness Error
4. Halo Error
5. Proximity Error
6. Contrast Error
7. Recency Effect
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- Your firm is conducting a study among employees about their attitudes toward union membership. Management needs a sampling design that is likely to reflect the true feelings of all employees but is efficient to draw. You must design a ____. Multiple Choice probability simple random sample nonprobability convenience sample nonprobability judgement sample probability cluster sample probability systematic sampleDevelop a Pareto chart of the following causes of poor grades on an exam: Choose the correct Pareto chart below. Number 1 2 3 4 5678 o 9 Reason for Poor Grade Insufficient time to complete Late arrival to exam Difficulty understanding material Insufficient preparation time Studied wrong material Distractions in exam room Calculator batteries died during exam Forgot exam was scheduled Felt ill during exam Frequency 67222SM. 15 25 9 1 3 4Figure 1 shows the general discriminatory test for health status prediction. "Perfect test cut-off True negative; TN (specificity) True positive; TP (sensitivity) False negative (FN) False positive (FP) Healthy Sick (a) Test cut-off Moving cut-off to left reduces false negatives (higher specificity) at cost of reduced sensitivity Moving cut-off to right reduces false positives (higher sensitivity) at cost of reduced specificity TN TP FN FP Healthy Sick (b) Figure 1. The Discriminatory Test with (a) A Good Discrimination Test Cut-off, and (b) A Bad Discrimination Test Cut-off i. What is your next action, if you obtain a perfect discriminatory test result (where both false negative and false positive rate are near zero) during model training? Justify your action. ii. In which phase of machine learning methodology do you move the test cut-off point as shown in Figure 1(b)? Justify why you should do that.
- Which best describes the null hypothesis associated with an Analysis of Variance (ANOVA)? Group of answer choices a. Ho: Variance 1 = Variance 2 = Variance 3 b. Ho: Standard Deviation 1 = Standard Deviation 2 = Standard Deviation 3 c. Ho: Proportion 1 = Proportion 2 = Proportion 3 d. Ho: Median 1 = Median 2 = Median 3 e. Ho: Mean 1 = Mean 2 = Mean 3Which of the following involves a test of two-related samples? Multiple Choice Test of whether the mean salary of professors at Metro University is higher than the national average for university professors Test of differences in the percent of men and women who are or are not members of Greek organizations on campus Test of whether a change occurred in the proneness for heart disease among people who switched to a diet high in fish Test of the average incomes of subscribers of Southern Living and Better Homes and Gardens Test of differences in ad recall among three experimental groups (each of which saw a different advertisement) and a control groupWhat is the centerline for the R chart? Group of answer choices a Less than 10 b Greater than or equal to 10 but less than 30 c Greater than or equal to 30 but less than 60 d Greater than or equal to 60 but less than 90 e Greater than or equal to 90
- 3) The major variable is the central idea of the entire literature. Its sub-variables help specify which particular aspect of the major variable is being referred to. The indicators, on the other hand, are specific information that describes the sub-variables. Examples: Major variable: Study habits Sub-variable: Time required for studying, methods of studying, and place for studying Indicators: Employing patterned time intervals for effective studying: using mnemonics in memorizing the terms; and studying in one's ideal environment Instructions: Identify the major variables, sub-variables, and indicators of the examples of literature review. Example 3: On leadership Competencies and Management Skills (refer to the photo for the details)10-Which one of the following is not an example of non-probability sampling technique? a. Convenience sampling b. Quota sampling c. Judgement sampling d. Cluster samplingIn what ways are the predictive and concurrent approaches to criterion-related validity the same? In what ways are these two approaches different?
- A technique for the study of interrelationships among variables, usually for the purposes of data reduction and the discovery of underlying constructs or latent dimensions is known as: a. Factor Analysis b. Structural Model Analysis c. Multiple linear regression d. Reliability AnalysisYou want to provide an overview of the characteristics of the respondents in your sample. Which of the following would you use to provide insight in the age of your respondents? a. A frequency table and a bar chart b. The mode, median and the standard deviation c. The mean and the variance. d. The mean, the median, and the modeHow might an Al algorithm decide or predict how much you liked what music you listened to on Alexa Music, Spotify or Pandora? (MA - pick all the answers that apply) O By just asking you after you listened to the music. By monitoring your facial expression and iris scan. By how long you replay the music. By monitoring the impact of the music's pitch, rhythm, and harmony to your neural (brain activity) along with your heat, sweat, and electrical responses to the music. By your first name. By your calculated personality profile prediction (a large pool of respondents survey O data that is matched to their Facebook likes and then applied to other profiles (including yours) and predicts how much you liked the music (with a high degree of accuracy). O By how many of your virtual friends on Facebook also like the same music. By how much you replay the music. By listening to your ultrasonic frequency while listening to music. O By your height, weight, and gender.