Tutorial Wk 8 Simple Linear Reg

TOPIC: Multivariable Functions in Economics

PRICE (Dollars per room) 500 450 400 350 300 250 200 150 100 50 0 Demand D 50 100 150 200 250 300 350 400 450 500 QUANTITY (Hotel rooms) Graph Input Tool Market for Oceans's Hotel Rooms Price (Dollars per room) Quantity Demanded (Hotel rooms per night) Demand Factors Average Income (Thousands of dollars) Airfare from MSY to ACY (Dollars per roundtrip) Room Rate at Meadows (Dollars per night) 350 150 50 200 250 ? For each of the following scenarios, begin by assuming that all demand factors are set to their original values and Oceans is charging $350 per room per night. If average household income increases by 20%, from $50,000 to $60,000 per year, the quantity of rooms demanded at the Oceans from rooms per night to rooms per night. Therefore, the income elasticity of demand is. , meaning that hotel rooms at the Oceans are If the price of an airline ticket from MSY to ACY were to increase by 10%, from $200 to $220 roundtrip, while all other demand factors remain at their initial values,…

Question: a) Calculate Regression Analysis of the data. b) Calculate Profit of a shop for 45 units sales

Topic: Regression    Problem 3:  A researcher is interested in determining whether there is a relationship between grades and hours studied for statistics.   Hours studied(X) Grade on final(Y) 1 20 2 30 4 40 7 60 6 70 7 78 8 83 9 98   1- You are given data for Xi (independent variable) and Yi (dependent variable).      2- Calculate the correlation coefficient, r:             r =           -1 ≤ r ≤ 1     3- Calculate the coefficient of determination: r2 = =                0 ≤ r2 ≤ 1 This is the proportion of the variation in the dependent variable (Yi) explained by the independent variable (Xi)                4- Calculate the regression coefficient b1 (the slope):              b1 = = Note that you have already calculated the numerator and the denominator for parts of r.  Other than a single division operation, no new calculations are required.   5- Calculate the regression coefficient b0 (the Y-intercept, or constant):…

Task II:Your manager asked you to answer the following:A) Define quantitative and qualitative data.B) Mention the differences between quantitative and qualitative data.C) Provide Real-World one example with Quantitative Data that could be presentedas a histogram (The example should contain the data collected + draw the frequency table for bothexamples).D) Provide Real-World one example with Qualitative Data that could be presented as a bar graph.(The example should contain the data collected + draw the frequency table for bothexamples). E) Use Excel software to represent the data in parts C and D.

:= 1:36 MicrolnternationalProject 5G 49 Done International Aspect of Project Homework Below is an except pasted from a semester project for this course (broken into two pieces). Your task is to respond to this prompt and to cite at least one source. For this assignment, the source may be scholarly or from a periodical. Your source should be documented as a reference using APA style. Be sure to respond to the prompt using concepts from our course. You may use models to illustrate your points. 1. American solar farms receive billions of dollars in taxpayer subsidies each year. These subsidies allow them to substitute grain production for energy production. How do U.S. solar farm subsidies hurt or benefit Mexican farmers? 2. What does this imply for U.S. food production independence? What could be done to address this problem, and would the solution be effective? Notice, having a positive effect, a negative effect or no net-effect is a possibility on Mexican farmers. Whatever your answer,…

Need graphs, as well as the following:

The table to the right contains price-demand and total cost data for the production of projectors, where p is the wholesale price (in dollars) of a projector for an annual demand of x projectors and C is the total cost (in dollars) of producing x projectors. Answer the following questions (A) - (D). (A) Find a quadratic regression equation for the price-demand data, using x as the independent variable. X 270 360 520 780 The fixed costs are $. (Round to the nearest dollar as needed.) ITTI y = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) Use the linear regression equation found in the previous step to estimate the fixed costs and variable costs per projector. The variable costs are $ per projector. (Round to the nearest dollar as needed.) (C) Find the break even points. The break even points are (Type ordered pairs. Use a comma to separate answers as needed. Round to the nearest integer as…

Construct a stem-and-leaf display, given the following data from a sample of midterm exam scores in finance: 51 64 97 70 99 52 52 82 70 O Fill in the stem-and-leaf display below. 5 (Do not use a comma to separate answers.)

Question 9 Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. Y = 120 - 15 X Based on the above estimated regression equation, if price is increased by 2 units, then demand is expected to: O Increase by 120 units Decease by 30 units O Increase by 2Q units Next « Previous Submi No new data to save. Last checked at 9:51pm

In the late 1980s land prices in Japan surged upward in a speculative bubble. Land prices then fell for 11 straight years between 1990 and 2001. What can we safely assume happened to land rent in Japan over those 11 years? Use graphical analysis to illustrate your answer.   graphical analysis is must, you have to draw graph.  Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.

Topic is information economics

1. A Travel-Cost Method Now it is time for your first consulting job as an environmental economist. The Forest Service would like to know whether they should preserve some national forest land, previously slated to be logged, for hiking. You are helping do a travel-cost analysis to estimate the annual benefits of hiking in this area. Survey data has been gathered from 500 hikers who visited the forest last year. This forest did not charge an entrance fee. Using a statistical technique called regression analysis, you have controlled for differences in income, employment status, age, and other important factors that might affect the number of hiking trips taken. Taking these factors into account, you have developed the following relationship: Zone 1 2 3 Population in zone 1,000 3.000 2,000 Cost Per Hiking Trip Per Person 20 40 80 Hiking Trips Taken Per Zonal Person Per Year 8 6 2 where cost includes gas, tolls, fares, hotels, entry fees, and the value of time spent traveling. a. Graph a…

1. A Travel-Cost Method Now it is time for your first consulting job as an environmental economist. The Forest Service would like to know whether they should preserve some national forest land, previously slated to be logged, for hiking. You are helping do a travel-cost analysis to estimate the annual benefits of hiking in this area. Survey data has been gathered from 500 hikers who visited the forest last year. This forest did not charge an entrance fee. Using a statistical technique called regression analysis, you have controlled for differences in income, employment status, age, and other important factors that might affect the number of hiking trips taken. Taking these factors into account, you have developed the following relationship: Zone Population in Cost Per Hiking Hiking Trips zone Trip Per Person Taken Per Zonal Person Per Year 1 1,000 2 3,000 3 2,000 20 8 40 6 80 2 where cost includes gas, tolls, fares, hotels, and the value of time spent traveling. a. Graph a linear…

2. Following is the summary of Eviews output for a multiple linear regression model where Y = annual household expenses (RM thousand) X1 = annual income (RM thousand) X2 = annual wealth (RM thousand) X3 = saving interest rate (%) Dependent Variable: LOG(Y) Sample: 1970 2019 Included observations: 50 Variable с LOG(X1) LOG(X2) X3 Coefficient -4.67711 8.04873 2.01270 -0.02689 Std. Error 2.41907 3.79049 1.24934 0.01361 0.789533 Durbin-Watson stat Adjusted R-squared S.E. of regression Sum squared resid 0.011934 Heteroskedasticity Test White 0.007121 Prob. Chi-Square (6) (a) Explain the meaning of the partial slope coefficient for LOG(X1) and X3. 1.589219 10.16032 0.0708 (b) At 10% significance level, do annual income and annual wealth, individually affect the annual household expenses? (c) Calculate the coefficient of determination and explain its meaning.

Graph Input Tool Market for Research Assistants 20 18 I Wage (Dollars per hour) 4 16 Labor Supplied (Number of workers) Supply Labor Demanded 500 14 (Number of workers) 12 Demand Shifter Supply Shifter 10 8 Demand Tax Levied on Employers (Dollars per hour) Tax Levied on Workers (Dollars per hour) 6. 4 40 80 120 160 200 240 280 320 360 400 LABOR (Number of workers) For each of the proposals, use the previous graph to determine the new number of research assistants hired. Then compute the after-tax amount paid by employers (that is, the wage paid to workers plus any taxes collected from the employers) and the after-tax amount earned by research assistants (that is, the wage received by workers minus any taxes collected from the workers). WAGE (Dollars per hour) +.--

团 jarb Hamed - A Find - eac Replace A Select - Editing Story: An E-Commerce portal has collected data regarding the customer activity on the website, app, and purchase portal. The portal management wanted to study the relationship between customers' length of Memberships and the yearly money amount spent by the customer buying stuff on their portal (The last two columns in the datasheet). Unfortunately, some information regarding some customers is missing e.g. Length of Membership. (A.) You have three approaches that needed to be tackled: 1) Fill the missing data using zeros 2) Fill the missing data using the mean of their column 3) Fill the missing data using the median of their column After trying each of them you need to study the effect of your new data proposition on the correlation between "Length of Membership" and "Yearly Amount Spent (B.) Using Principal Components Analysis (PCA), Reduce the number of independent variables to only two(use any library you want for PCA) Data:…

System of Equations: p=6−2q p=2+q Plot both equations on a graph. The values of pp and qq that solve these two equations simultaneously can be seen on the graph as A. the inverse of the slopes of the two lines B. the slopes of the two lines C. the coordinates at which the two lines intersect D. the value of the intercepts of the two lines

d/My courses / Faculty Of Economics & Administratiive Sciences / ECON309 / Finals / ECON 309 Fin 13. In the simple linear regression model, the regression slope a. O a. indicates by how many percent Y increases, given a one percent increase in X. ut of O b. represents the elasticity of Y on X. uestion Oc. when multiplied with the explanatory variable will give you the predicted Y. O d. indicates by how many units Y increases, given a one unit increase in X. nage

In the late 1980s land prices in Japan surged upward in a speculative bubble. Land prices then fell for 11 straight years between 1990 and 2001. What can we safely assume happened to land rent in Japan over those 11 years? Use graphical analysis to illustrate your answer.   Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.

d. If the director used these 4 weeks of data to create a linear regression, what does that linear regression formula suggest for this week's forecast of employee appointments? What does the regression analysis suggest in general about employee appointments for Director Very Busy?

1. Explain the meaning of: R-SQUARED F-TEST MULTICOLLINEARITY   2. Why are these considered as more important in multiple regression analysis? 3. How to detect problems in multicollinearity?

9. The (incomplete) table below shows the x and y values for three data points. It also shows the estimated coefficients, predicted y values and residuals for two potential regression lines (A and B). Fill in the missing values in the table below. obs 1 W23 2 3 100 90 80 70 60 50 40 30 20 10 0 y 60 20 0 1 X 3 2 8 Using the values you just calculated, plot the three data points and the two estimated regression equations in the graph below. Be sure to label everything clearly VA 40 50 3 aA A BA Regression A UA 4 -30 -15 5 10 YB 6 40 60 B Regression B A Вв 7 UB 25 -20 15 8 20 9 10

ECON131: Quantitative Methods in Economics – Business and Finance Assignment The City of Sydney is an area covering over 26km2 and is one of Australia’s most important social and economic centres. As part of Sydney 2030, a study into the city’s long-term sustainability, the city council committed to reducing its carbon footprint 70% over the next 20 years. A study found that around 31% of the city’s carbon emissions arise from public lighting. So, in 2011, the City of Sydney announced a project to replace its lighting systems with energy efficient LED lights. It would choose lighting systems based on both their economic and environmental value. After a consultation period, the City chose a supplier in late 2011 to replace 6,448 luminaries (lights).Before the project, suppose that the 6,448 luminaries slated for replacement consumed 5,252,613 kWh of electricity annually. In 2010/11, the annual lighting bill was $654,476. Suppose that the new LED…

2. Which of the following types of regressions will always have a binary outcome variable? (A) Probit (B) Difference-in-differences (C) Regression discontinuity (D) (A) and (B) will both have binary outcome variables

Table 4.1 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.99794806 Missing 0.99513164 Standard Error 1.64839211 Observations 20 ANOVA Significance F af Missing 16 19 MS F Regression 10561.07486 Missing 1295.585 2.66E-19 Residual 43.47514498 2.717197 Total 10604.55 Coefficients 0.562 Standard Error t Stat P-Value Intercept X1 1.327 0.424 0.677 0.959 0.038 25.245 0.000 X2 1.117 0.125 8.916 0.000 X3 1.460 0.066 22.185 0.000 Consider the output shown in Table 4.1. Which of the predictors has the greatest impact on the dependent variable? X2 Intercept X1 X3

ST History Bookmarks People Tab Window Help Take a Test - Ashley Kong a mathxl.com/Student/PlayerTest.aspx?testld=221340504¢erwin=yes Calculus (MAT 103) Ashley Kong :| 10/06/20 11:39 PM Quiz: Chapter 2 Homework Submit Quiz This Question: 18 of 26 (17 complete) v This Quiz! The price, in dollars per units, that consumers are willing to pay for a popular high-end digital camera units. Complete parts (a) and (b). given by the accompanying function, where x is in thousands of p(x) = 1520 -185 In x a) What price corresponds to a demand of 290,000 units? How can the price that corresponds to a demand of 290,000 units be found? Select the correct choice below and fill in the answer box to complete your choice. (Simplify your answer.) O A. Evaluate p() O B. Solve = 1520 - 185 In x for x The price that corresponds to a demand of 290,000 units is $. (Round to the nearest cent as needed.) b) How many units will consumers buy at a price of $850 per camera? How can the number of units that…

1. An analyst from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Price of X Income 0.38 0.14 0.13 20.77 150 df 2 147 149 SS 58.87 -1.64 1.11 10398.87 63408.62 73807.49 Coefficients Standard Error 15.33 0.85 0.24 MS 5199.43 431.35 t Stat 3.84 -1.93 4.63 F 12.05 P-value 0.00 0.06 0.00 Significance F 0 Lower 95% 28.59 -3.31 0.63 Upper 95% b. Which regression coefficients are statistically significant at the 5 percent level? a. Based on these estimates, write an equation that summarizes the demand for the firm's product. 89.15 0.04 1.56 C. When price is $10, what is the income elasticity for this product for an income level of 35?

10- What would be the consequences for the OLS estimator if heteroskedasticity is present in a regression model but ignored?* a. It will be biased b. It will be inconsistent c. It will be inefficient d. All of (a), (b), and (c) will be true

Only typed answer and please don't use chatgpt otherwise I downvote the answer  Assume that the relationship between test scores and the student-teacher ratio can be modeled as a linear function with an intercept of 698.9 and a slope of (-2.28). A decrease in the student teacher ratio by 2 will:   A) reduce test scores by 2.28 on average   B) result in a test score of 698.9   C) reduce test scores by 2.56 on average   D) reduce test scores by 4.56 for every school district   PLEASE EXPLAIN WHY C IS CORRECT.

Time left U:18:05 CLEAR MY CHOICE Finish a Question Consider the following model Y=B1+B2 X2 +e. Assume you change the scale of the y and X variables in such a way that Not yet Y*=aY and X2*=bX2. and you run the regression Y*=B1*+B2* X". What effect this scaling will have on answered the slope Marked out of 1.00 Select one: P Flag O a. B2=a+b (B2) question O b. B2*=a/b^2 (B2) O c. B2*-ab (B2) O d. B2*=a/b (B2) NEXT PAGE PREVIOUS PAGE

Topic: Geometric Gradient Series

WHERE IS THE CHART COMING FROMIAM CONFUSED? FC=1200? PLEASE EXPLAIN CHART USED AC=FC/Q+VC (600x3.1) - (500x3.5) 110 = 11 600-500 100 3.10= UC/600+11 3.50=UC/500+1.10 FC=1200 EURO FC=1200 EURO AC=UC/Q+VC UC=UNIT COST