Quiz 6

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University of California, Los Angeles *

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100A

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Psychology

Date

Dec 6, 2023

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pdf

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Time Remaining: 21:48 Time Remaining: 21:46 Below is a summary of your responses Download PDF We thank you for your time spent taking this survey. Your response has been recorded. Welcome to Psych 100A Quiz (Chapter 9). Work your way through all the questions first, to make sure you don't run out of time. Then go back and think more about the ones you aren't sure of. Each question is worth one point (except when otherwise indicated). Check all that apply questions include a small penalty for checking incorrect options. If you are having trouble with R, you can use the R- sandbox or Rstudio. You may use your textbook, R Cheatsheet , Google, or any other resources (other than people) to help. I recommend you use Chrome for completing the quiz. You can still close and reopen this link without affecting the time you have to complete the quiz. Keeping Time: There is a timer at the top of the quiz page. If you close the window and open it again, the clock will restart. However, data is only recorded up until 3000 seconds after you started the timer on the first window. Data is collected on the time from start to finish of your quiz, and if more than 3000 seconds passes between when you start and end the quiz you will receive a 0 on the quiz. What is your First Name? What is your Last Name? What is your 9-digit student ID? (Please include only the digits, no dashes, commas, or spaces; and please use leading zeros so your ID has exactly 9 digits (e.g., 123456789). You can use the R-sandbox or Rstudio. You may use your textbook, R Cheatsheet , Google, or any other resources (other than people) to help. Sean Park 405406173

Select the correct general linear model for a model with a quantitative outcome variable and a quantitative explanatory variable. Select the correct general interpretation of b0 from a general linear model with a quantitative predictor. Select the correct general interpretation of b1 from a general linear model with a quantitative predictor. Which of the following is an ADVANTAGE of using a variable as a quantitative predictor compared to a qualitative predictor? The predicted score for the reference group. The predicted score on Y for a case with a score of 0 on X. The sample average of Y. The average for the group of people who score 0 on X. The predicted score on Y for a case with a score of 0 on X. The correlation between X and Y. The increment by which you change the predicted Y for each one unit increase in X. The difference between the two group averages. The model is more complex (more model degrees of freedom) Being able to make a prediction for all observed scores The model is less complex (fewer model degrees of freedom) Being able to capture non-linear relationships

Match the following hypotheses to signs for b1. Assume the variables in the parentheses are X and Y Which of the following is NOT true about the correlation between two variables X and Y? Cricket Data The next few questions all apply to the following dataset: The data were collected by E.A. Bessey and C.A. Bessey who measured chirp rates for crickets and temperatures during the summer of 1898. The data frame CricketChirps has 7 observations on the following 2 variables. : Temperature Air temperature in degrees F Chirps Cricket chirp rate (chirps per minute) Crickets: In the research question "Can the temperature predict the chirp rate of crickets?" Match the explanatory and the outcome variable and to the notation from the GLM Positive b1 Negative b1 b1 = 0 Knowing someone's grade in Psych 100A doesn't help us predict their grade in Psych 100B (Grade in 100A, Grade in 100B) Children get taller as they get older (Height and Age) People who exercise more are less likely have have a heart attack (Amount of Exercise, Heart Attack) It is equal to PRE If we square the correlation it will be equal to PRE It is the same as the correlation between Y and X It is the same as the correlation between Y and the predicted Y from a model where X is a quantitative predictor of Y (i.e., Yhat) Chirps Temperature Explanatory Variable

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Crickets: Which of the following visualizations would be helpful in visualizing a quantitative predictor model for the relationship between temperature and chirps. Crickets: Fit a linear model predicting Chirps from Temperature. Select the estimate for b0. Crickets: Fit a linear model predicting Chirps from Temperature. Select the estimate for b1. Crickets: Based on the linear model you fit above, what is the predicted score chirps per minute when the temperature is 80 degrees F. Explanatory Variable Outcome Variable Chirps Temperature Histogram Boxplot Point Plot / Scatter Plot All of the above 4.25 -157.82 37.68 0.23 4.25 0.23 37.68 -157.82 161.26 182.53 129.35 139.98

Crickets: Based on the results from the linear model, the correlation between Chirps and Temperature will be .... Sean: You are at the end of the quiz. Do not click the red Submit arrow until you are done with the exam. Are you done with your exam? If yes, click "Yes, I am done!" below, and then click the red Submit arrow. (If you are not done go back and review your previous answers.) You are now done with the quiz. You cannot return to your previous questions. Please answer the following questions about your experience with this quiz. As a reminder, you are not required to answer these questions. They are part of a research study. Answering or not answering these questions will not impact your grade . How difficult did you find the questions on this quiz? How well do you think you learned the course content addressed by these questions? 139.98 Positive Negative Zero We can't tell from the linear model Yes, I am done! Very easy Easy Medium Somewhat difficult Difficult Not well at all Somewhat well Well Very well

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