estimated the following multiple regression model using yearly data spanning the period 2001 toWhere FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processedA researcher interested in explaining the level of foreign reserves for the country of Barbados2016:FR=a+B0IL+YEXP+8FDIusing MINITAB and the following is an extract of the output oblamed.PredictorCoefStDevp-valuet-ratio5491.38 2508.81 2.1888Constant0.0491OIL85.3918.464.6260.0006EXP-377.08 112.190.0057FDI-396.99 160.66-2.471S = 2.45R-sq = 96.3%R-sq (adj) = 95.3%Analysis of VarianceSourceDFSMSFRegression663.77??31991.31Error1277.46.45Total15d) Hence test whether B is significant. Give reasons for your answer.e) Perform the F Test making sure to state the null and alternative hypothesis.f) Given an interpretation of the term "R-sq" and comment on its value.

A researcher interested in explaining the level of forcign reserves for the country of Barbadon estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: Where FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports FR=a+BOIL+YEXP+&FDI ($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 0.0491 2.1888 OIL 85.39 18.46 4.626 0.0006 EXP 08 . ר37- 112.19 0.0057 FDI -396.99 ** 160.66 -2.471 S = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source MS F P DF Regression 3 663.77 ?? 1991.31 Error 12 77.4 6.45 Total 15 d) Hence test whether B is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term "R-sq" and comment on its value.

A researcher interested in explaining the level of forcign reserves for the country of Barbadon estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: Where FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports FR=a+BOIL+YEXP+&FDI ($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 0.0491 2.1888 OIL 85.39 18.46 4.626 0.0006 EXP 08 . ר37- 112.19 0.0057 FDI -396.99 ** 160.66 -2.471 S = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source MS F P DF Regression 3 663.77 ?? 1991.31 Error 12 77.4 6.45 Total 15 d) Hence test whether B is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term "R-sq" and comment on its value.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Q: Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in…

A: Given plot is number of vehicle Registration in millions Vs Year and there a black color straight…

Q: A study was conducted on 64 female college athletes. The researcher collected data on a number of…

A: In Linear regression, we partition the total variability in the model into two parts: explained and…

Q: The following regression equation is based on the analysis of four variables: SM_DOLLARS is the…

A: The regression equation is given as : WEB_VISITS(expected)=208+0.75×SM_DOLLARS+1.5…

Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…

A: Here Yearly foreign reserves is the dependent variable and Annual oil prices, Yearly total exports…

Q: Define Time-lagged regression analysis?

A: Introduction The time series data is consists of a sequence of data values indexed in time order.

Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…

A: c) Given: Coeff of (EXP) B=-377.08 stdev = 112.19 The missing value of "*" The t-ratio for the…

Q: Consider a multiple regression model for predicting the total number of runs scored by a Major…

A: Since you have posted a question with multiple sub-parts, we will solve the first three subparts for…

Q: Explain which characteristic of the STA leads to a consideration of a logistic model as opposed to a…

A: In a standardized test, the outcome of interest is typically whether a student passes or fails the…

Q: The following linear regression model predicts a person's height (cm) from the length of their shoe…

A: given linear regression model is Height = 3.5 x shoe print + 80 predicted height = ? shoe print =…

Q: Apple CAPM Data file posted on has data about the monthly return on Apple Inc. from 1981 to 2005…

A: To address the given task, we need to analyze the monthly return data for Apple Inc. from 1981 to…

Q: In the picture, there is a summary of regression analysis. Please interpret the P values for each…

A: The p-values corresponding to each coefficient implies, if there is a significance of the particular…

Q: researcher collects some socioeconomic variables of Turkey and wants to model the natural gas…

A: Given table depicts the coefficients of variables and their statistical parameters. The researcher…

Q: Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to…

Q: A data set consists of the following ordered pairs: {(0, 8), (2, 11), (6, 17), (8, 20), (9,…

A: Consider the following table: There are 5 data set pairs given. Thus, n =5.

Q: A company randomly samples 48 months of monthly output and monthly total cost data. The sampled data…

A: The Company's fixed cost is given as the Intercept of the regression Model. Hence, the fixed cost is…

Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…

A: e) The null and alternate hypothesis are H0 : β1=β2=...=βk=0H0 : βi≠0 for atleast for one i, 1≤i≤k…

Q: Explain how to choose the dependent and independent variables in regression analysis used for…

A: Regression analysis: Regression analysis estimates the relationship among variables. That is, it…

Q: For the population of Jellystone bears, the mean weight is 600 pounds and the mean blood pressure is…

A: Given, Mean weight is 600 pounds Mean pressure is 150 slope of SLR for response variable blood…

Q: true or false. Explain In a fixed effects regression, the residuals (ûit) will be uncorrelated with…

A: The statement is true.

Q: An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size…

A: The response variable is Rent($) and the predictor variable is Size(ft2). The fitted model is : Rent…

Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…

A: Solution From the given output The regression equation is FR= 5491.38 + 85.39OIL - -377.08EXP…

Q: A clothing manufacturer wants to estimate the amount of scrap cloth generated each day by its fabric…

A: Given : Source of variation Degrees of freedom Sum of Squares Mean squares F-statistic…

Q: Suppose there is a significant correlation between variables. describe 2 instances in which it…

A: Given: The material of choice for the microelectronics applications includes the single crystal…

Q: g multiple regression model using yearly data spanning the period 2001 to2016: ??=?+????+????+????…

A: Here we have given processed data of sample Predictor Coef StDev…

Q: Define regression line

A: Suppose ,we have 2 variables X and Y, out of which we want to know if there is any linear dependency…

Q: The investigators for a study collected standardized data on timed 24-hour urinary excretion for…

A: sub-parts."}"…

Q: Suppose there is a significant correlation between two variables. Describe a case under which it…

A: 2 cases where a significant correlation between 2 variables need not make one a predictive factor…

Q: he following regression equation is based on the analysis of four variables: SM_DOLLARS is the…

A: It is given the regression equation is: WEB_VISITS=109+0.2×SM_DOLLARS+1.5×RADIO_ADS+1.1×WS_DOLLARS

Q: In the regression model established in the study conducted on 114 employees in India, the variables…

A: A regression is a technique in statistics that relates a dependent and independent variable. In this…

Q: The following regression equation is based on the analysis of four variables: SM_DOLLARS is the…

A: The fitted line is: WEB_VISITS= 208 + 1.5*SM_DOLLARS + 0.5*RADIO_ADS +…

Q: A researcher interested in explaining the level of foreign reserves for the country of Barbados…

A: Note: Hey there Thank you for the question. As you have posted multiple sub-parts, we have helped…

Q: Hobust standard errors are given in parentheses under coefficients. e following statements correctly…

A: we have given above the few regressions of the total cost of states

Q: estimated the following multiple regression model using yearly data spanning the period 2001 2016:…

A: The null and alternative hypotheses are The test statistic is given by t = 4626 p-value = 0.006…

Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

estimated the following multiple regression model using yearly data spanning the period 2001 to
Where FR = yearly foreign reserves ($000's), OIL = annual oil prices, EXP = yearly total exports
($000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed
A researcher interested in explaining the level of foreign reserves for the country of Barbados
2016:
FR=a+B0IL+YEXP+8FDI
using MINITAB and the following is an extract of the output oblamed.
Predictor
Coef
StDev
p-value
t-ratio
5491.38 2508.81 2.1888
Constant
0.0491
OIL
85.39
18.46
4.626
0.0006
EXP
-377.08 112.19
0.0057
FDI
-396.99 160.66
-2.471
S = 2.45
R-sq = 96.3%
R-sq (adj) = 95.3%
Analysis of Variance
Source
DF
S
MS
F
Regression
663.77
??
3
1991.31
Error
12
77.4
6.45
Total
15
d) Hence test whether B is significant. Give reasons for your answer.
e) Perform the F Test making sure to state the null and alternative hypothesis.
f) Given an interpretation of the term "R-sq" and comment on its value.

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

SEE SOLUTION Check out a sample Q&A here

Step 1

Step 2

Step 3

Step 4

Step 5

Step by step

Solved in 5 steps with 2 images

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Correlation, Regression, and Association$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.

Similar questions

The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table. Time Miles Load Speed Oil 7.7 42.9 22.0 44.0 16.0 0.8 98.3 20.0 47.0 34.0 6.3 61.1 22.0 62.0 15.0 E Click here for the Excel Data File b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Time = Miles Load Speed oil + + d. What is the predicted time before the first engine overhaul for a particular truck driven 60,000 miles per year with an average load of 25 tons, an average driving speed of 53 mph, and 21,000 miles…
Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"+ describes a study to investigate the effect of frying time (in seconds) and acrylamide concentration (in micrograms per kilogram) in french fries. The data in the accompanying table are approximate values read from a graph that appeared in the paper. Frying Acrylamide Time Concentration 150 240 240 270 300 300 150 125 + 195 185 135 275 USE SALT (a) Find the equation of the least-squares line for predicting acrylamide concentration using frying time. (Round your answers to four decimal places.) ŷ = (b) Does the equation of the least-squares line support the conclusion that longer frying times tend to be paired with higher acrylamide concentrations? Explain. O No, the least squares regression line…
11. What is the standard error of the slope of the regression line (SEb)? Please put the answer in bold.
Explain how to determine the variance inflation factor (VIF) for a predictor variable x1 in a regression equation that also contains the predictor variables x2, x3, and x4.
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the equation of the resulting multiple linear regression? starting_salary = 3008.61 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15000.00 + 48.65*GPA + 94.79*years_of_experience + 27.36*civil_service_ratings starting_salary = 15001.00 + 41.43*GPA + 84.71*years_of_experience + 37.32*civil_service_ratings starting_salary = 2366.77 + 130.25*GPA + 396.39*years_of_experience + 21.67*civil_service_ratings
Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
A researcher interested in explaining the level of foreign reserves for the country of Barbadosestimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+????Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained:Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491OIL 85.39 18.46 4.626 0.0006EXP -377.08 112.19 * 0.0057FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq = 96.3% R-sq(adj) = 95.3%Analysis of VarianceSource DF SS MS F pRegression 3 1991.31 663.77 ? ??Error 12 77.4 6.45Total 15 Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq” and comment on its value.
Please look at the following regression table. The year is 2010. The data originates from the Penn World Table 9.0, from Harris et.al. 2014 from the World Bank and from the International Energy Agency. The variables are defined as follows: Lntran_pc = log of transportation energy consumption per capita (ktoe) Lnypcpenn =log of GDP per capita (USD) Ln_gasprice = log of pump price for gasoline (USD/liter) Ln_temperature = log of the average annual temperature (in C) Ln_annualprecip= log of annual precipitation (mm) Ln_land = log of the land area of a country OECD = a dummy (indicator) that takes on the value of 1 if the country is OECD member, zero otherwise. Please define (Gauss Markov) MLR 4, state if it is likely to hold or not in this case.
A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+B0IL+YEXP+8FDI Where FR = yearly foreign reserves ($000°s), OIL = annual oil prices, EXP = yearly total exports ($000's) and FDI = annual foreign direct investment ($000`s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 ** s = 2.45 R-sq = 96.3% R-sq (adj) = 95.3% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation
The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…