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P(A) =
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In Algebra there are constants and variables. 'p' is a variable which means that its value can change with reference to the equation it is present in.
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University of New Hampshire Quick Logic Proof Questions
Quick question about logic, which won't take 10mins if you are good at solving it. Please using the formate which the samp ...
University of New Hampshire Quick Logic Proof Questions
Quick question about logic, which won't take 10mins if you are good at solving it. Please using the formate which the sample shows, which the step by step. And there are some rules to help you to explain the each steps. Please give me the quality answer as soon as possible.
Econometrics Solution, statistics homework help
*** You can use any statis tic software to solve (SPSS, Eviews, R...)*** The result of each problem must contain RESULT TA ...
Econometrics Solution, statistics homework help
*** You can use any statis tic software to solve (SPSS, Eviews, R...)*** The result of each problem must contain RESULT TABLE (from the software) and EXPLANATION (Short or long)*** The data file is in .xls form (Excel needed)Background A good understanding of the macroeconomic cycle with alternating recession and expansion periods (also known as the business cycle) is important for various decision makers. Macroeconomic policy is often based on predictions of this cycle, and such predictions can influence investment decisions of large companies. Central banks and other institutions often publish so-called leading indicators that are helpful to predict the state of the economy. These indicators are based on macroeconomic series like job formation, interest rates, credit, demand, and supply. In this case project you will predict GDP growth by using quarterly data on a hypothetical economy from 1950 quarter 1 to 2015 quarter 4. The data set contains the GDP of the economy and two leading indicators li1 and li2. In order to evaluate the predictive performance of econometric models, you need to split the data in two parts. As estimation sample you take the period from 1951 to 2010 (240 observations), and as evaluation sample you take the period from 2011 to 2015 (20 observations). The first year of data (1950) is used only to create lags of variables. The project consists of two parts. In the first part (a-c) you use logit models to predict whether the economic situation improves or declines, and in the second part (d-g) you use time series models to predict the size of the growth rate of the economy.Data The data file Case GDP contains the following variables: • DATE: Date of the observation; • GDP: Gross Domestic Product of the economy; • GDPIMPR: dummy variable indicating whether the GDP has increased (1) or decreased (0); • LOGGDP: Log of Gross Domestic Product; • GrowthRate: Relative growth of the economy: GrowthRatet = log(GDPt ) − log(GDPt−1); • li1: First leading indicator; • li2: Second leading indicator; • T: Linear trend (where the first observation, for 1950 quarter 1, is defined as 0).(a) The table below summarizes the outcomes of four logit models to explain the direction of economic development (GDPIMPR) for the period 1951 to 2010. Perform three Likelihood Ratio tests to prove both the individual and the joint significance of the 1-quarter lags of li1 and li2, where the alternative hypothesis is always the model with both indicators included. (Please see image name TABLE 1)b) It could be that the leading indicators lead the economy by more than 1 quarter. The table below summarizes outcomes of four logit models that differ in the lags of the indicators. For what reason can we use McFadden R2 to select the best lag structure among these four models? Compute the four values of McFadden R2 (with four decimals) and conclude which model is optimal according to this criterion. (Please see image name TABLE 2)(c) Use the logit model 3 of part (b) (with li1(-2) and li2(-1)) to calculate the predicted probability of economic growth for each of the 20 quarters of the evaluation sample. Assess the predictive performance by means of the prediction-realization table and the hit rate, using a cut-off value of 0.5. Evaluate the outcomes.(d) Perform the Augmented Dickey-Fuller test on LOGGDP to confirm that this variable is not stationary. Use only the data in the estimation sample and include constant, trend, and a single lag in the test equation (L = 1, see Lecture 6.4). Present the coefficients of the test regression and the relevant test statistic, and state your conclusion.(e) Consider the following model: GrowthRatet = α + ρGrowthRatet−1 + β1li1t−k1 + β2li2t−k2 + εt . Here the numbers k1 and k2 denote the lag orders of the leading indicators. Estimate four versions of this model on the estimation sample from 1951 to 2010, by setting k1 and k2 equal to either 1 or 2. Show that the model with k1 = k2 = 1 gives the largest value for R2, and present the four coefficients of this model in six decimals. (f) Perform the Breusch-Godfrey test for first-order residual serial correlation for the model in part (e) with k1 = k2 = 1. Does the test outcome signal misspecification of the model?(g) Use the model in part (e) with k1 = k2 = 1 to generate a set of twenty one-step-ahead predictions for the growth rates in each quarter of the period 2011 to 2015. Note that the required values of the lagged leading indicators are available for each of these forecasts. Calculate the root mean squared error of these forecasts and present a time series graph of the predictions and the actual growth rates.
MAT 243 SNHU Applied Statistics Supervised & Unsupervised Machine Learning Essay
CompetencyIn this project, you will demonstrate your mastery of the following competency:Perform regression analysis to ad ...
MAT 243 SNHU Applied Statistics Supervised & Unsupervised Machine Learning Essay
CompetencyIn this project, you will demonstrate your mastery of the following competency:Perform regression analysis to address an authentic problemScenarioYou are a data analyst for a basketball team and have access to a large set of historical data that you can use to analyze performance patterns. The coach of the team and your management have requested that you come up with regression models that predict the number of wins in a regular game based on the performance metrics that are included in the data set. These regression models will help make key decisions to improve the performance of the team. You will use the Python programming language to perform the statistical analyses and then prepare a report of your findings to present for the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications.Note: This data set has been “cleaned” for the purposes of this assignment.ReferenceFiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye...DirectionsFor this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.Python Script: Python script complete! See attached pictures!Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:Introduction: Set the context for your scenario and the analyses you will be performing.Scatterplots and Correlation: Discuss relationships between variables using scatterplots and correlation coefficients.Simple Linear Regression: Create a simple linear regression model to predict the response variable.Multiple Regression: Create a multiple regression model to predict the response variable.Conclusion: Summarize your findings and explain their practical implications.What to SubmitTo complete this project, you must submit the following:Summary Report Zip File Word DocumentUse the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.Supporting MaterialsThe following resource(s) may help support your work on the project:Shapiro Library: APA Style GuideThis guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.
Algebra 2 - Unit Circle, Special Triangles, algebra homework help
Complete each set of problems. LINK -- http://ogburn.org/wp-content/uploads/2016/05/AlgII...
Algebra 2 - Unit Circle, Special Triangles, algebra homework help
Complete each set of problems. LINK -- http://ogburn.org/wp-content/uploads/2016/05/AlgII...
STAT KSU Small Values of Baseline Curvature and Baseline Refractive Error Questions
Dataset “EX0812.txt” is posted in folder “datasets”. Use SAS, fit a model relating change in refractive error to ...
STAT KSU Small Values of Baseline Curvature and Baseline Refractive Error Questions
Dataset “EX0812.txt” is posted in folder “datasets”. Use SAS, fit a model relating change in refractive error to baseline refractive error and baseline curvature.Examine the plot of the residuals versus the predicted values. Are any regression assumption violations apparent? If so, suggest possible remedies.Determine residuals and leverage values. Do any observations seem bothersome? Explain. (Hint: Myopic patients have negative refractive errors).
Table design, graph assignment help
During your weekly trip to the grocery store, you purchase bread, milk, cold cereal, bananas, and ice cream. The purchase ...
Table design, graph assignment help
During your weekly trip to the grocery store, you purchase bread, milk, cold cereal, bananas, and ice cream. The purchase was made using a debit card.Create a table listing at least seven data items collected in this transaction and how they are entered into the system.Submit your table in a Word document or on an Excel® spreadsheet to the Assignment Files tab above.
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Most Popular Content
University of New Hampshire Quick Logic Proof Questions
Quick question about logic, which won't take 10mins if you are good at solving it. Please using the formate which the samp ...
University of New Hampshire Quick Logic Proof Questions
Quick question about logic, which won't take 10mins if you are good at solving it. Please using the formate which the sample shows, which the step by step. And there are some rules to help you to explain the each steps. Please give me the quality answer as soon as possible.
Econometrics Solution, statistics homework help
*** You can use any statis tic software to solve (SPSS, Eviews, R...)*** The result of each problem must contain RESULT TA ...
Econometrics Solution, statistics homework help
*** You can use any statis tic software to solve (SPSS, Eviews, R...)*** The result of each problem must contain RESULT TABLE (from the software) and EXPLANATION (Short or long)*** The data file is in .xls form (Excel needed)Background A good understanding of the macroeconomic cycle with alternating recession and expansion periods (also known as the business cycle) is important for various decision makers. Macroeconomic policy is often based on predictions of this cycle, and such predictions can influence investment decisions of large companies. Central banks and other institutions often publish so-called leading indicators that are helpful to predict the state of the economy. These indicators are based on macroeconomic series like job formation, interest rates, credit, demand, and supply. In this case project you will predict GDP growth by using quarterly data on a hypothetical economy from 1950 quarter 1 to 2015 quarter 4. The data set contains the GDP of the economy and two leading indicators li1 and li2. In order to evaluate the predictive performance of econometric models, you need to split the data in two parts. As estimation sample you take the period from 1951 to 2010 (240 observations), and as evaluation sample you take the period from 2011 to 2015 (20 observations). The first year of data (1950) is used only to create lags of variables. The project consists of two parts. In the first part (a-c) you use logit models to predict whether the economic situation improves or declines, and in the second part (d-g) you use time series models to predict the size of the growth rate of the economy.Data The data file Case GDP contains the following variables: • DATE: Date of the observation; • GDP: Gross Domestic Product of the economy; • GDPIMPR: dummy variable indicating whether the GDP has increased (1) or decreased (0); • LOGGDP: Log of Gross Domestic Product; • GrowthRate: Relative growth of the economy: GrowthRatet = log(GDPt ) − log(GDPt−1); • li1: First leading indicator; • li2: Second leading indicator; • T: Linear trend (where the first observation, for 1950 quarter 1, is defined as 0).(a) The table below summarizes the outcomes of four logit models to explain the direction of economic development (GDPIMPR) for the period 1951 to 2010. Perform three Likelihood Ratio tests to prove both the individual and the joint significance of the 1-quarter lags of li1 and li2, where the alternative hypothesis is always the model with both indicators included. (Please see image name TABLE 1)b) It could be that the leading indicators lead the economy by more than 1 quarter. The table below summarizes outcomes of four logit models that differ in the lags of the indicators. For what reason can we use McFadden R2 to select the best lag structure among these four models? Compute the four values of McFadden R2 (with four decimals) and conclude which model is optimal according to this criterion. (Please see image name TABLE 2)(c) Use the logit model 3 of part (b) (with li1(-2) and li2(-1)) to calculate the predicted probability of economic growth for each of the 20 quarters of the evaluation sample. Assess the predictive performance by means of the prediction-realization table and the hit rate, using a cut-off value of 0.5. Evaluate the outcomes.(d) Perform the Augmented Dickey-Fuller test on LOGGDP to confirm that this variable is not stationary. Use only the data in the estimation sample and include constant, trend, and a single lag in the test equation (L = 1, see Lecture 6.4). Present the coefficients of the test regression and the relevant test statistic, and state your conclusion.(e) Consider the following model: GrowthRatet = α + ρGrowthRatet−1 + β1li1t−k1 + β2li2t−k2 + εt . Here the numbers k1 and k2 denote the lag orders of the leading indicators. Estimate four versions of this model on the estimation sample from 1951 to 2010, by setting k1 and k2 equal to either 1 or 2. Show that the model with k1 = k2 = 1 gives the largest value for R2, and present the four coefficients of this model in six decimals. (f) Perform the Breusch-Godfrey test for first-order residual serial correlation for the model in part (e) with k1 = k2 = 1. Does the test outcome signal misspecification of the model?(g) Use the model in part (e) with k1 = k2 = 1 to generate a set of twenty one-step-ahead predictions for the growth rates in each quarter of the period 2011 to 2015. Note that the required values of the lagged leading indicators are available for each of these forecasts. Calculate the root mean squared error of these forecasts and present a time series graph of the predictions and the actual growth rates.
MAT 243 SNHU Applied Statistics Supervised & Unsupervised Machine Learning Essay
CompetencyIn this project, you will demonstrate your mastery of the following competency:Perform regression analysis to ad ...
MAT 243 SNHU Applied Statistics Supervised & Unsupervised Machine Learning Essay
CompetencyIn this project, you will demonstrate your mastery of the following competency:Perform regression analysis to address an authentic problemScenarioYou are a data analyst for a basketball team and have access to a large set of historical data that you can use to analyze performance patterns. The coach of the team and your management have requested that you come up with regression models that predict the number of wins in a regular game based on the performance metrics that are included in the data set. These regression models will help make key decisions to improve the performance of the team. You will use the Python programming language to perform the statistical analyses and then prepare a report of your findings to present for the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications.Note: This data set has been “cleaned” for the purposes of this assignment.ReferenceFiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye...DirectionsFor this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.Python Script: Python script complete! See attached pictures!Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:Introduction: Set the context for your scenario and the analyses you will be performing.Scatterplots and Correlation: Discuss relationships between variables using scatterplots and correlation coefficients.Simple Linear Regression: Create a simple linear regression model to predict the response variable.Multiple Regression: Create a multiple regression model to predict the response variable.Conclusion: Summarize your findings and explain their practical implications.What to SubmitTo complete this project, you must submit the following:Summary Report Zip File Word DocumentUse the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.Supporting MaterialsThe following resource(s) may help support your work on the project:Shapiro Library: APA Style GuideThis guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.
Algebra 2 - Unit Circle, Special Triangles, algebra homework help
Complete each set of problems. LINK -- http://ogburn.org/wp-content/uploads/2016/05/AlgII...
Algebra 2 - Unit Circle, Special Triangles, algebra homework help
Complete each set of problems. LINK -- http://ogburn.org/wp-content/uploads/2016/05/AlgII...
STAT KSU Small Values of Baseline Curvature and Baseline Refractive Error Questions
Dataset “EX0812.txt” is posted in folder “datasets”. Use SAS, fit a model relating change in refractive error to ...
STAT KSU Small Values of Baseline Curvature and Baseline Refractive Error Questions
Dataset “EX0812.txt” is posted in folder “datasets”. Use SAS, fit a model relating change in refractive error to baseline refractive error and baseline curvature.Examine the plot of the residuals versus the predicted values. Are any regression assumption violations apparent? If so, suggest possible remedies.Determine residuals and leverage values. Do any observations seem bothersome? Explain. (Hint: Myopic patients have negative refractive errors).
Table design, graph assignment help
During your weekly trip to the grocery store, you purchase bread, milk, cold cereal, bananas, and ice cream. The purchase ...
Table design, graph assignment help
During your weekly trip to the grocery store, you purchase bread, milk, cold cereal, bananas, and ice cream. The purchase was made using a debit card.Create a table listing at least seven data items collected in this transaction and how they are entered into the system.Submit your table in a Word document or on an Excel® spreadsheet to the Assignment Files tab above.
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