### Understanding the Impact of Attendance on Student Performance#### Problem StatementA college professor was becoming annoyed by how many of his students were absent during his 8:00 a.m. section of Philosophy 103. He decided to analyze whether these absences were impacting student scores. He assigned his TA the task of keeping track of attendance. At the end of the semester he compared each student’s grade on the final exam (100 points possible) with the number of times he or she had been absent. His findings are displayed in the graph to the right.#### Analysis Tasksa) **Identify the explanatory and response variables.**b) **Describe the relationship between these two variables.** - **Form** - **Direction** - **Strength** - **Outliers**c) **Jeremy was absent 25 times. What would you predict his score on the final exam to be?**d) **Lucy often overslept and missed 43 class sessions. What would you predict for her score on the final?**#### Graph Analysis: Absences & Final Exam Scores- **Title**: Absences & Final Exam Scores- **X-Axis**: Number of Absences (87 total days)- **Y-Axis**: Grade on Final ExamThe scatter plot presents the grades of students on the final exam as a function of the number of absences. There is a negatively sloped trend line represented by the equation \( \hat{y} = 91.704 - 1.654x \) with an \( R^2 \) value of 0.8732.**Key Observations**:- **Form**: The relationship appears to be linear, as indicated by the straight-line trend.- **Direction**: The trend is negative, implying that more absences are associated with lower final exam scores.- **Strength**: With an \( R^2 \) value of 0.8732, the data points show a strong fit to the trend line, indicating a strong linear relationship between absences and final exam scores.- **Outliers**: There do not appear to be significant outliers that deviate from the trend considerably.Using the trend line equation \( \hat{y} = 91.704 - 1.654x \):- **For Jeremy (25 absences)**: \[ \hat{y} = 91.704 -

The object is to infer the nature of the relationship between "no. of absent days" and the "final…

Answered: 6.3 7) A college professor was becoming…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The number of pair days off taken by eight employees at a local small business is compared to the national average. You are hired by the business owner, who has been in business for just 18 months, to help her determine what to expect for paid days off. In general, she wants to set some standard for her employees and for herself. Let's assume your search on the internet for data on paid days off leaves you with the impression that the national average is 15 days. The data for the eight local employees during the last fiscal year are: 10, 11, 8, 14, 13, 12, 12, and 27 days. 1. Calculate the appropriate t statistic. 2. Draw a statistical conclusion. 3. Calculate and interpret the effect size.
On fan sites, there were discussions about whether the data show a home-field advantage: does the host team tend to perform better than the visiting teams? In order to answer this question, you dedicate some time to watching all 8 of the Marbula one races. For each race, you record TRUE if the host team finishes in the top 2, and FALSE otherwise. Remember, there are 16 teams competing in each race. In 2 of the 8 races, the host team finished in the top 2. You conduct a simulation of this experiment: 1000 sets of 8 races using the null proportion = a. (You need to determine the correct value of a). Of the 1000 simulated experiments shown below, you find that in b simulations, there are at least 2 races where the host team finished in the top 2. (You determine the value of b) Simulation results Sim mean: 0.98 n= 402 400- Sim sd: 0.93 n = 350 300 - 200- n= 177 100- n= 59 n- 12 # Races where host team finished in the top 2 Which of the following statements are correct? # Simulations
2. A real estate expert wanted to find the relationship between the sale price of houses and various characteristics of the houses. He collected data on five variables, recorded in the table, for 12 houses that were sold recently. The five variables are: Sale price of a house in thousands of dollars. Size of the lot in acres. Price: Lot Size: Living Area: Living area in square feet. Age: Type of house: town house (T) or Villa (V) Age of a house in years. Living Area Price Lot Size Age Туре of house 255 1.4 2500 8 T 178 0.9 2250 12 263 1.8 2900 127 0.7 1800 24 305 2.6 3200 10 164 1.2 2400 18 245 2.1 2700 9 146 1.1 2050 28 287 2.8 2850 13 189 1.6 2600 9 211 1.7 2300 8. 123 0.5 1700 11 a) Find the general regression equation b) Which independent variables are linearly related to price? c) How is the fit of the model? E BBBB BB>>}>> >{
During one shift, the express lane clerk recorded how many times customers violated the "10 items or less" rule for his lane. In particular, he recorded how many items over the limit each violator placed on the conveyor belt. This data is summarized in the histogram below. NOTE: The last class actually represents "7 or more items," not just 7 items. Frequency 12+ 298 ans = 10- a 2 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 # items over 10 What is the frequency of times the limit was exceeded by at least 3 items?
lecture(12.9): Identify the following variables as categorical or numerical. (a) Th ethnicity of the individual respondents in a political poll of randomly selected group of adults. (b) the income amount of the individual respondents in a political poll of randomly selected group of individuals. (c) The gender of children who have completed Peacock Picture Test.
6. After 5 tests Michael has a mean score of 87%. There is one more test to take. What is the minimum score that Michael needs to keep a B (80%)? What is the minimum score Michael needs to raise his grade to an A (90%)?
A study found that 50 pedestrians gave more money to a street beggar if the beggar had a cute and hungry-looking dog with them compared to if they were alone. The gender of the pedestrians was also noted. Which of the following sentences describes a simple effects analysis on these data? Oa. The difference in donations when the beggar had a dog compared to not Ob. The effect of having a dog compared to not on donations calculated separately for male and female pedestrians Oc. The relative difference between male donations and female donations when the beggar had a dog compared to not Od. Using a graph to do a simple inspection of the mean donations from male and female pedestrians when the beggar had a dog or was alone
Do iii and iv.
Please make sure the response is specific to the variables in this problem: Imagine that you are interested in studying the working habits of young adults. You hypothesize that persons first married in their twenties tend to work an average of 5 hours more per week than persons not first married in their twenties. After conducting a survey study, you find a relationship between participants’ age at first marriage and the number of hours worked per week. What three conditions must be satisfied for you to have established a causal connection?
2. A real estate expert wanted to find the relationship between the sale price of houses and various characteristics of the houses. He collected data on five variables, recorded in the table, for 12 houses that were sold recently. The five variables are: Sale price of a house in thousands of dollars. Size of the lot in acres. Price: Lot Size: Living Area: Living area in square feet. Age: Type of house: town house (T) or Villa (V) Age of a house in years. Price Lot Size Living Area Age Туре of house 255 1.4 2500 8 T 178 0.9 2250 12 T T. T. T. 263 1.8 2900 5 0.7 2.6 127 1800 24 305 3200 10 164 1.2 2400 18 245 2.1 2700 T V 146 1.1 2050 28 287 2.8 2850 13 V 189 1.6 2600 9 211 1.7 2300 8 V 123 0.5 1700 11 V a) Find the regression equation for the town house b) Find the regression equation for the Villa c) What is the price of a town house with a lot size of 1.3, living area of 1800, and is 7 years old? EBBBBE A> >}>l> >{
For which reason is it a problem when journalists only report on one study? a. It can lead people to think journalists are scientists. b. It can cause people to interrogate a study’s validities. c. It can lead people to value one study over decades of previous research. d. It can make journalists look bad.
A professor has a class with five recitation sections. Each section has 18 students. The question is whether or not the average test score is significantly different for any of the sections. Group-1 Group-2 Group-3 Group-4 Group-5 83.7 84.3 56.6 67.5 60.7 80.8 77.1 83 71.9 80.2 91.3 72.4 77.4 70.5 57.3 80.1 74.4 79.2 79 68.7 93.3 71.9 73 81.8 70 78.1 73.7 74.5 62.8 64.5 76.5 69.7 81.4 75.1 63.1 68.2 72 75.2 83.7 65.5 62.8 71 79.3 85.4 67.6 76.5 73.1 74.5 81.5 67.1 79.2 67.9 74.9 86.7 72.2 62.1 78.7 84.8 63.4 80.8 86.7 97.2 66.8 79.3 68.2 79 74.6 66.4 75.9 67.7 79.1 82.3 69.3 70.3 68.2 71.1 62.2 53.3 71.1 58 61.8 68.9 82.7 60.2 73 70.7 83.2 61.9 64.6 49.5 Conduct a test to determine if the group means are equal using α=0.02α=0.02. Summary statistics:F-ratio (F-test statistics) = p-value = (report accurate to at least 4 decimal places)What is the measure of effect size ω2ω2 ? This is on the Excel sheet and is also a measure of the…

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