How are they used? – 2 years ago
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– 2 years ago
In-depth study guidance and analytical solution covering week 9 Discussion & Reflection.
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[>Criminal homework help](https://www.sweetstudy.com/fields/law-criminal) Students will engage in a **virtual courtroom ethics simulation** where they take on different legal roles (judge, prosecutor, defense attorney, or defendant) and analyze ethical dilemmas from Chapter 8. #### **Instructions:**…
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Students will engage in a **virtual courtroom ethics simulation** where they take on different legal roles (judge, prosecutor, defense attorney, or defendant) and analyze ethical dilemmas from Chapter 8.
#### **Instructions:**
– Each student will select one of the following roles:
– **Judge** – Ensures fairness and decides on the ethical implications of legal decisions.
– **Prosecutor** – Must seek justice while upholding ethical rules.
– **Defense Attorney** – Defends the client while balancing moral and legal responsibilities.
– **Defendant** – Must navigate legal advice and ethical choices.
– Read the **case scenario** below and analyze the ethical dilemmas from the perspective of your assigned role.
writing a script.
– 2 years ago
In-depth study guidance and analytical solution covering week 3 re.
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[>American history homework help](https://www.sweetstudy.com/fields/history-american-history) help with history – 2 years ago
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help with history
– 2 years ago
**this week's discussion, we will collaboratively create a measure of self-esteem.** 1. Provide a working definition of self-esteem. 2. Indicate the type of response format that you would recommend for our instrument (for example, Likert-scale, open-ended, true-false, multiple choice) 3. Discuss you…
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Order on TutorsGallery →**this week's discussion, we will collaboratively create a measure of self-esteem.**
1. Provide a working definition of self-esteem.
2. Indicate the type of response format that you would recommend for our instrument (for example, Likert-scale, open-ended, true-false, multiple choice)
3. Discuss your approach to item construction. In other words, describe the process you use to generate items for our instrument.
4. List at least five items we could include in our new self-esteem scale.
Hi Class,
I mentioned in the live session this week that there are some issues with reverse-scored items. I am attaching an article here that goes more in depth regarding these issues.
Given the challenges with reverse scored items, please have all 5 of your suggestions have phrasing in a forward manner (I know I mentioned it might be good to have one reverse scored, but let's keep consistent and just have all items in the same direction). Any questions, let me know!
Reference
van Sonderen, E., Sanderman, R., & Coyne, J.C. (2013). Ineffectiveness of reverse wording of questionnaire items: Let’s learn from cows in the rain. _PLOS One, 8_(7), e68967.
[van Sonderen et al. (2013) Ineffectiveness of reverse wording.pdf](https://keiseruniversity.blackboard.com/courses/1/RSM815G3-103102025/db/_27059105_1/van%20Sonderen%20et%20al.%20%282013%29%20Ineffectiveness%20of%20reverse%20wording.pdf) (97.847 KB)
Complete the following readings from your textbook, _Psychological Testing: A Practical Approach to Design and Evaluation:_
– Chapter 2
– Chapter 3
– [\
\
KeyConceptsinPsychologicalTestingDiscussion4.docx](https://www.sweetstudy.com/files/keyconceptsinpsychologicaltestingdiscussion4-docx "KeyConceptsinPsychologicalTestingDiscussion4.docx")
– [\
\
en-Week2.txt](https://www.sweetstudy.com/files/en-week2-txt-10231047 "en-Week2.txt")
– 2 years ago
– 2 years ago **files (3)** – ## Assignment2.pdf – hprice1.xlsx – RandomNumbers.xlsx **## Assignment2.pdf** Assignment 2 ECO 562 Due: Sunday 3/23 11:59pm on D2L [5 Points] 1. Suppose that you are interested in determining the effect of adding a bedroom on the price of your house with sales data (…
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**files (3)**
– ## Assignment2.pdf
– hprice1.xlsx
– RandomNumbers.xlsx
**## Assignment2.pdf**
Assignment 2
ECO 562
Due: Sunday 3/23 11:59pm on D2L
[5 Points]
1. Suppose that you are interested in determining the effect of adding a bedroom on the
price of your house with sales data (Hprice.xlsx). Using GPT 4o/4.5, es mate the naïve
regression [provide the link to full chat below]:
price = 𝑚 ∗ bedrooms + 𝑏 + �̃� (1)
Link:
a. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (1). If there are viola ons to either assump on, fix it in the chat provided
above. If there are no issues, proceed to part b.
b. [0.5 Points] What is the interpreta on of the es mated values of 𝑚 and 𝑏, including
the p-values? [No AI allowed]
c. [0.5 Points] Why did we test for viola ons of OLS before interpre ng the es mated
coefficients 𝑚 and 𝑏? [No AI allowed]
d. [0.5 Points] What does it mean for 𝑚 to be unbiased? [No AI allowed]
e. [0.5 Points] Why might the square footage of the house be an omi ed variable from
the regression (1)? In other words, if the only objec ve is to determine the effect of
adding one more bedroom on the price of the house, why would the square footage
need to be included in the regression for the es mates to be unbiased? [No AI
allowed]
Using GPT 4o/4.5, es mate the regression below [es mate should be in the same chat as the
link above]:
price = 𝑚 ∗ bedrooms + 𝑚 ∗ square footage + 𝑏 + 𝑒 (2)
f. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (2). If there are viola ons to either assump on, fix it in the chat link
provided above. If there are no issues, proceed to part g.
g. [0.5 Points] What is the interpreta on of the es mates 𝑚 and 𝑚 , including the p-
values? [No AI Allowed]
h. [0.5 Points] How does 𝑚 and 𝑚 compare? Why does including square footage in the
regression affect the marginal effect of the number of bedrooms
posi vely/nega vely? [No AI Allowed]
2. To demonstrate the weakness of measure 𝑅 as a measure of goodness-of-fit in the
context of regression analysis, consider Random Numbers.xlsx.
ChatGPT Link:
a. [0.25 Points] Using GPT 4o/4.5, create a correla on table and matrix of Y and X1,
X2,…, X50. What is the intrinsic rela onship between Y and the 50 X’s? [Hint: the
spreadsheet is called ‘Random Numbers’]
b. [0.25 Points] Ask GPT 4o/4.5 to es mate the regressions (copy and paste the
quoted below into the chat):
“Es mate the regressions
Y=m1*X1+b+e
Y=m1*X1+ m2*X2+b+e
Y=m1*X1+ m2*X2+ m3*X3+b+e
…
Y=m1*X1+ m2*X2+ m3*X3+…+ m50*X50+b+e
For each regression, collected the r-squared. Plot the es mated r-square as a func on of
the number of uncorrelated independent variables.”
Describe the plot created with this prompt.
c. [0.5 Points] How does this exercise relate to the concept of a Kitchen Sink
Regression?
**hprice1.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/hprice1-xlsx)
**RandomNumbers.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/randomnumbers-xlsx)
**RandomNumbers.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/randomnumbers-xlsx)
**## Assignment2.pdf**
Assignment 2
ECO 562
Due: Sunday 3/23 11:59pm on D2L
[5 Points]
1. Suppose that you are interested in determining the effect of adding a bedroom on the
price of your house with sales data (Hprice.xlsx). Using GPT 4o/4.5, es mate the naïve
regression [provide the link to full chat below]:
price = 𝑚 ∗ bedrooms + 𝑏 + �̃� (1)
Link:
a. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (1). If there are viola ons to either assump on, fix it in the chat provided
above. If there are no issues, proceed to part b.
b. [0.5 Points] What is the interpreta on of the es mated values of 𝑚 and 𝑏, including
the p-values? [No AI allowed]
c. [0.5 Points] Why did we test for viola ons of OLS before interpre ng the es mated
coefficients 𝑚 and 𝑏? [No AI allowed]
d. [0.5 Points] What does it mean for 𝑚 to be unbiased? [No AI allowed]
e. [0.5 Points] Why might the square footage of the house be an omi ed variable from
the regression (1)? In other words, if the only objec ve is to determine the effect of
adding one more bedroom on the price of the house, why would the square footage
need to be included in the regression for the es mates to be unbiased? [No AI
allowed]
Using GPT 4o/4.5, es mate the regression below [es mate should be in the same chat as the
link above]:
price = 𝑚 ∗ bedrooms + 𝑚 ∗ square footage + 𝑏 + 𝑒 (2)
f. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (2). If there are viola ons to either assump on, fix it in the chat link
provided above. If there are no issues, proceed to part g.
g. [0.5 Points] What is the interpreta on of the es mates 𝑚 and 𝑚 , including the p-
values? [No AI Allowed]
h. [0.5 Points] How does 𝑚 and 𝑚 compare? Why does including square footage in the
regression affect the marginal effect of the number of bedrooms
posi vely/nega vely? [No AI Allowed]
2. To demonstrate the weakness of measure 𝑅 as a measure of goodness-of-fit in the
context of regression analysis, consider Random Numbers.xlsx.
ChatGPT Link:
a. [0.25 Points] Using GPT 4o/4.5, create a correla on table and matrix of Y and X1,
X2,…, X50. What is the intrinsic rela onship between Y and the 50 X’s? [Hint: the
spreadsheet is called ‘Random Numbers’]
b. [0.25 Points] Ask GPT 4o/4.5 to es mate the regressions (copy and paste the
quoted below into the chat):
“Es mate the regressions
Y=m1*X1+b+e
Y=m1*X1+ m2*X2+b+e
Y=m1*X1+ m2*X2+ m3*X3+b+e
…
Y=m1*X1+ m2*X2+ m3*X3+…+ m50*X50+b+e
For each regression, collected the r-squared. Plot the es mated r-square as a func on of
the number of uncorrelated independent variables.”
Describe the plot created with this prompt.
c. [0.5 Points] How does this exercise relate to the concept of a Kitchen Sink
Regression?
**hprice1.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/hprice1-xlsx)
**RandomNumbers.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/randomnumbers-xlsx)
**## Assignment2.pdf**
Assignment 2
ECO 562
Due: Sunday 3/23 11:59pm on D2L
[5 Points]
1. Suppose that you are interested in determining the effect of adding a bedroom on the
price of your house with sales data (Hprice.xlsx). Using GPT 4o/4.5, es mate the naïve
regression [provide the link to full chat below]:
price = 𝑚 ∗ bedrooms + 𝑏 + �̃� (1)
Link:
a. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (1). If there are viola ons to either assump on, fix it in the chat provided
above. If there are no issues, proceed to part b.
b. [0.5 Points] What is the interpreta on of the es mated values of 𝑚 and 𝑏, including
the p-values? [No AI allowed]
c. [0.5 Points] Why did we test for viola ons of OLS before interpre ng the es mated
coefficients 𝑚 and 𝑏? [No AI allowed]
d. [0.5 Points] What does it mean for 𝑚 to be unbiased? [No AI allowed]
e. [0.5 Points] Why might the square footage of the house be an omi ed variable from
the regression (1)? In other words, if the only objec ve is to determine the effect of
adding one more bedroom on the price of the house, why would the square footage
need to be included in the regression for the es mates to be unbiased? [No AI
allowed]
Using GPT 4o/4.5, es mate the regression below [es mate should be in the same chat as the
link above]:
price = 𝑚 ∗ bedrooms + 𝑚 ∗ square footage + 𝑏 + 𝑒 (2)
f. [0.5 Points] Using GPT 4o/4.5, test for heteroscedas city and linearity of the
regression (2). If there are viola ons to either assump on, fix it in the chat link
provided above. If there are no issues, proceed to part g.
g. [0.5 Points] What is the interpreta on of the es mates 𝑚 and 𝑚 , including the p-
values? [No AI Allowed]
h. [0.5 Points] How does 𝑚 and 𝑚 compare? Why does including square footage in the
regression affect the marginal effect of the number of bedrooms
posi vely/nega vely? [No AI Allowed]
2. To demonstrate the weakness of measure 𝑅 as a measure of goodness-of-fit in the
context of regression analysis, consider Random Numbers.xlsx.
ChatGPT Link:
a. [0.25 Points] Using GPT 4o/4.5, create a correla on table and matrix of Y and X1,
X2,…, X50. What is the intrinsic rela onship between Y and the 50 X’s? [Hint: the
spreadsheet is called ‘Random Numbers’]
b. [0.25 Points] Ask GPT 4o/4.5 to es mate the regressions (copy and paste the
quoted below into the chat):
“Es mate the regressions
Y=m1*X1+b+e
Y=m1*X1+ m2*X2+b+e
Y=m1*X1+ m2*X2+ m3*X3+b+e
…
Y=m1*X1+ m2*X2+ m3*X3+…+ m50*X50+b+e
For each regression, collected the r-squared. Plot the es mated r-square as a func on of
the number of uncorrelated independent variables.”
Describe the plot created with this prompt.
c. [0.5 Points] How does this exercise relate to the concept of a Kitchen Sink
Regression?
**hprice1.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/hprice1-xlsx)
**RandomNumbers.xlsx**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/randomnumbers-xlsx)
[>Operations Management homework help](https://www.sweetstudy.com/fields/business-finance-operations-management) **Conduct internet research and give examples, support, and explain your answers and positions.** **Include and Answer the following questions:** 1. Go to the website of a major brand of …
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**Conduct internet research and give examples, support, and explain your answers and positions.**
**Include and Answer the following questions:**
1. Go to the website of a major brand of HRT CBO (Company, Business, Organization).
Explain how it appeals to different segments through the website. Give specific examples.
2. Choose another HRT CBO you are familiar with.
Explain at least two (2) of the segments in its overall market. Using one (1) of the markets, explain how it differentiated itself from its competitors to position itself in the market.
3. Visit the annual report of an HRT CBO through their website.
What does the annual report tell you about the CBO’s strategy?
Reference
Godin, S. (2018). This is marketing. Portfolio Penguin. ISBN: 978-0-525-54083-0
– 2 years ago
Will share the instructions with the right person. – 2 years ago
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– 2 years ago