ECONOMETRIC PROJECT-Econ325 [Autosaved].pptx
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This is the econometrics research project i which, a sample of 26 people was where we calculate the relationship between stationary and and the monthly pocket money of collage students
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The effect of investment on school building and student performanc.docx
The effect of investment on school building and student performance
1. Statement of the problem
This paper will address the effect of investment on school facilities to student performance. We are interested especially in seeing whether additional money spend on school buildings lead to improvement of student performance, keeping every other factors constant.
2. Review of the literature
There are a lot of literature which attempted to explain the effects of school resources on student performance, but the relationship between school resources and student performance has been controversial. First of all, Hanushek (1997) provided huge volume of literature review about the effects of school resources on student performance. After review of around 400 previous studies of student achievement, he found that there is not a strong or consistent relationship between student performance and school resources including the real resources of the classroom (teacher education, teacher experience, and teacher-pupil ratios), financial aggregates of resources (expenditure per student and teacher salary), and measures of other resources in school (specific teacher characteristics, administrative inputs, and facilities).
On the other hand, Eide and Showalter (1998) studied the effect of school quality on student performance. In this paper, they found that the number of school enrollment and school year length have positive relation with student performance. They also observed that there may be differential school quality effects at different points in the test score gain conditional distribution.
Wӧßmann (2003) investigated that the effects of family background, resources and institutions on students’ mathematics and science performance using an international database of more than 260,000 students from 39 countries. His result showed that international differences in student performance cannot be attributed to resource differences, but they are considerably related to institutional differences. He found that centralized examinations and control mechanisms, school autonomy in personnel and process decisions, individual teacher influence over
teaching methods, limits to teacher unions’ influence on curriculum scope, scrutiny of students’ achievement and competition from private schools have positive effects on the student performance.
3. The data
The data for this paper consists of 1,967 observations of Ohio Elementary School buildings for 2001-2002 year. For each observation we have 1) the number of teachers, 2) teacher attendance rate, 3) average years of teaching experience, 4) average teacher salary, 5) per pupil spending on instruction, 6) per pupil spending on building operations, 7) per pupil spending on administration, 8) per pupil spending on pupil support, 9) per pupil spending on staff support, 10) median of 4th grade prof scores(student performance), 11) building enrollment, 12) per capita income in the zip code area, 13) percent of p ...
An AHP (Analytic Hierarchy Process) Based Investment Strategy for Charitable ...
This paper provides the optimal investment strategy for the Goodgrant Foundation. To determine the schools to be invested, firstly we find the factors about improving students’ educational performance, including urgency of student’s needs, school’s demonstrate potential for effective use of private funding,
the reputation of school, and return on investment etc; secondly, we utilize AHP (Analytic Hierarchy Process) to determine the weight of every factor and rank the schools in the list of candidate schools according to the composite index of every school calculated from the weight. To confirm the investment per school and obtains the investment duration time, we use DEA (Data Envelope Analyse) to get changes of scale efficiency; and then according to the change trend, we determine time duration of investment and effective utilization of private funding, which is the factor together with student population affecting the
investment amount for per school. It is helpful to make a better decision on investing universities, We are convinced that our research is promising to benefit all sides of students, schools and Goodgrant.
AN AHP(ANALYTIC HIERARCHY PROCESS)-BASED INVESTMENT STRATEGY FOR CHARITABLE O...
This paper provides the optimal investment strategy for the Goodgrant Foundation. To determine the
schools to be invested, firstly we find the factors about improving students’ educational performance,
including urgency of student’s needs, school’s demonstrate potential for effective use of private funding,
the reputation of school, and return on investment etc; secondly, we utilize AHP (Analytic Hierarchy
Process) to determine the weight of every factor and rank the schools in the list of candidate schools
according to the composite index of every school calculated from the weight. To confirm the investment per
school and obtains the investment duration time, we use DEA (Data Envelope Analyse) to get changes of
scale efficiency; and then according to the change trend, we determine time duration of investment and
effective utilization of private funding, which is the factor together with student population affecting the
investment amount for per school. It is helpful to make a better decision on investing universities, We are
convinced that our research is promising to benefit all sides of students, schools and Goodgrant.
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I created this presentation as a final project for the subject of Inferential Statistics. It defines the different hypothesis, inferential statistics, regression analysis, the use of dependent and independent variables. It also consists an example of these theories at the end.
Let me know in the comments if you want me to upload a video of myself presenting this presentation.
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The effect of investment on school building and student performanc.docx
The effect of investment on school building and student performance
1. Statement of the problem
This paper will address the effect of investment on school facilities to student performance. We are interested especially in seeing whether additional money spend on school buildings lead to improvement of student performance, keeping every other factors constant.
2. Review of the literature
There are a lot of literature which attempted to explain the effects of school resources on student performance, but the relationship between school resources and student performance has been controversial. First of all, Hanushek (1997) provided huge volume of literature review about the effects of school resources on student performance. After review of around 400 previous studies of student achievement, he found that there is not a strong or consistent relationship between student performance and school resources including the real resources of the classroom (teacher education, teacher experience, and teacher-pupil ratios), financial aggregates of resources (expenditure per student and teacher salary), and measures of other resources in school (specific teacher characteristics, administrative inputs, and facilities).
On the other hand, Eide and Showalter (1998) studied the effect of school quality on student performance. In this paper, they found that the number of school enrollment and school year length have positive relation with student performance. They also observed that there may be differential school quality effects at different points in the test score gain conditional distribution.
Wӧßmann (2003) investigated that the effects of family background, resources and institutions on students’ mathematics and science performance using an international database of more than 260,000 students from 39 countries. His result showed that international differences in student performance cannot be attributed to resource differences, but they are considerably related to institutional differences. He found that centralized examinations and control mechanisms, school autonomy in personnel and process decisions, individual teacher influence over
teaching methods, limits to teacher unions’ influence on curriculum scope, scrutiny of students’ achievement and competition from private schools have positive effects on the student performance.
3. The data
The data for this paper consists of 1,967 observations of Ohio Elementary School buildings for 2001-2002 year. For each observation we have 1) the number of teachers, 2) teacher attendance rate, 3) average years of teaching experience, 4) average teacher salary, 5) per pupil spending on instruction, 6) per pupil spending on building operations, 7) per pupil spending on administration, 8) per pupil spending on pupil support, 9) per pupil spending on staff support, 10) median of 4th grade prof scores(student performance), 11) building enrollment, 12) per capita income in the zip code area, 13) percent of p ...
An AHP (Analytic Hierarchy Process) Based Investment Strategy for Charitable ...
This paper provides the optimal investment strategy for the Goodgrant Foundation. To determine the schools to be invested, firstly we find the factors about improving students’ educational performance, including urgency of student’s needs, school’s demonstrate potential for effective use of private funding,
the reputation of school, and return on investment etc; secondly, we utilize AHP (Analytic Hierarchy Process) to determine the weight of every factor and rank the schools in the list of candidate schools according to the composite index of every school calculated from the weight. To confirm the investment per school and obtains the investment duration time, we use DEA (Data Envelope Analyse) to get changes of scale efficiency; and then according to the change trend, we determine time duration of investment and effective utilization of private funding, which is the factor together with student population affecting the
investment amount for per school. It is helpful to make a better decision on investing universities, We are convinced that our research is promising to benefit all sides of students, schools and Goodgrant.
AN AHP(ANALYTIC HIERARCHY PROCESS)-BASED INVESTMENT STRATEGY FOR CHARITABLE O...
This paper provides the optimal investment strategy for the Goodgrant Foundation. To determine the
schools to be invested, firstly we find the factors about improving students’ educational performance,
including urgency of student’s needs, school’s demonstrate potential for effective use of private funding,
the reputation of school, and return on investment etc; secondly, we utilize AHP (Analytic Hierarchy
Process) to determine the weight of every factor and rank the schools in the list of candidate schools
according to the composite index of every school calculated from the weight. To confirm the investment per
school and obtains the investment duration time, we use DEA (Data Envelope Analyse) to get changes of
scale efficiency; and then according to the change trend, we determine time duration of investment and
effective utilization of private funding, which is the factor together with student population affecting the
investment amount for per school. It is helpful to make a better decision on investing universities, We are
convinced that our research is promising to benefit all sides of students, schools and Goodgrant.
Hypothesis Testing Project - Inferential Statistics
I created this presentation as a final project for the subject of Inferential Statistics. It defines the different hypothesis, inferential statistics, regression analysis, the use of dependent and independent variables. It also consists an example of these theories at the end.
Let me know in the comments if you want me to upload a video of myself presenting this presentation.
EFFECTIVENESS OF INTEGRATING RIDDLES IN TEACHING MATHEMATICS AMONG VIII STAND...
Mathematics is considered as dry subject and students do not find anything interesting in it. This impression about Mathematics can be reversed with the help of recreational activities in Mathematics. The present study tries to find out the effectiveness of integrating riddles in teaching mathematics among eighth standard students. Two equivalent group experimental-designs are employed for this study. The investigator has chosen 40 eighth standard students for the study. According to the scoring of pre-test, 20 students were chosen as control group and 20 students were chosen as experimental group. Finally the investigator concludes; (a) There is a significant difference between the means of students thought through conventional method and puzzles and riddles way of learning group. (b) There is a significant difference between the means of the Post-Test scores of control group and experimental group students with respect to the knowledge, understanding and application objectives.
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Title Page in APA style with Running HeadAPA style AbstractInt.docx
Title Page in APA style with Running Head
APA style Abstract
Introduction
(Enter information in a bulleted format. Each bullet should be followed by 2-4 sentences.)
*NOTE: This first table is an example. You will need to delete the information in the table then, enter your question & data.
Results
Question: What is the relationship between academic interest and academic performance?
Allen & Robbins (2010)
Background Theory/Past Research Quote: Page 24
“When applied to students in postsecondary education, Holland’s theory suggests that students are more likely to be satisfied and succeed when their interests are congruent with their academic environments (Smart, Feldman, & Ethington, 2000).”
“In another study, first-year GPA and a measure of interest–major congruence both had relatively large effects on whether students changed major, suggesting that students with greater interest–major congruence are (a) more satisfied with their academic program and (b) more likely to graduate in a timely fashion due to not changing majors (Allen & Robbins, 2008).”
Background Theory/Past Research: Page 24
Students are more likely to do well in college when their interests are related to their major and academic environment (Smart, Feldman, & Ethington as cited in Allen & Robbins, 2010). Students whose major and interests are closely related are likely to graduate more quickly because of their low likelihood of changing majors (Allen & Robbins as cited in Allen & Robbins, 2008).
Research Hypothesis Quote:
Page 25
“Thus, we hypothesize that higher interest–major congruence has a positive effect on first-year academic performance. By virtue of having greater satisfaction with students’ major, Holland’s theory also suggests that greater interest–major congruence will lead to students satisfying their degree requirements earlier.”
“Thus, our second hypothesis is that interest–major congruence has a positive direct affect on timely degree attainment (beyond the effects of first-year academic performance).”
Research Hypothesis:
Page 25
Students with higher interest-major congruence will do better in their first year at college. Also, Allen & Robbins hypothesized that students with higher interest-major congruence will also earn their degree faster.
Methods Quote:
Page 26-8
“Furthermore, 3,860 (3,072 four-year and 788 two-year) of these students began as full-time students with expectations of earning at least a bachelor’s (4-year) or certificate (2-year) degree. This is the sample of students on which this study is based.”
“To be included in the study sample, students must (a) have taken the ACT tests of educational achievement and completed the Unisex Edition of the ACT Interest Inventory (UNIACT; ACT, 1995) when registering for the ACT;”
“The edition of UNIACT used in this study has 90 items (15 per scale) that describe work-relevant activities that are familiar to people either through participation or observation. For each item, students indicate wheth ...
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Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations if the models are statistically significant. Delete instructions and examples highlighted in yellow before submitting this assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1:There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, ...
12Insert Title HereInsert Your Name HereInsert
1
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations if the models are statistically significant. Delete instructions and examples highlighted in yellow before submitting this assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1:There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, ...
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Unlock the potential of Latino Buying Power with this in-depth SlideShare presentation. Explore how the Latino consumer market is transforming the American economy, driven by their significant buying power, entrepreneurial contributions, and growing influence across various sectors.
**Key Sections Covered:**
1. **Economic Impact:** Understand the profound economic impact of Latino consumers on the U.S. economy. Discover how their increasing purchasing power is fueling growth in key industries and contributing to national economic prosperity.
2. **Buying Power:** Dive into detailed analyses of Latino buying power, including its growth trends, key drivers, and projections for the future. Learn how this influential group’s spending habits are shaping market dynamics and creating opportunities for businesses.
3. **Entrepreneurial Contributions:** Explore the entrepreneurial spirit within the Latino community. Examine how Latino-owned businesses are thriving and contributing to job creation, innovation, and economic diversification.
4. **Workforce Statistics:** Gain insights into the role of Latino workers in the American labor market. Review statistics on employment rates, occupational distribution, and the economic contributions of Latino professionals across various industries.
5. **Media Consumption:** Understand the media consumption habits of Latino audiences. Discover their preferences for digital platforms, television, radio, and social media. Learn how these consumption patterns are influencing advertising strategies and media content.
6. **Education:** Examine the educational achievements and challenges within the Latino community. Review statistics on enrollment, graduation rates, and fields of study. Understand the implications of education on economic mobility and workforce readiness.
7. **Home Ownership:** Explore trends in Latino home ownership. Understand the factors driving home buying decisions, the challenges faced by Latino homeowners, and the impact of home ownership on community stability and economic growth.
This SlideShare provides valuable insights for marketers, business owners, policymakers, and anyone interested in the economic influence of the Latino community. By understanding the various facets of Latino buying power, you can effectively engage with this dynamic and growing market segment.
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USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
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Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
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EFFECTIVENESS OF INTEGRATING RIDDLES IN TEACHING MATHEMATICS AMONG VIII STAND...
Mathematics is considered as dry subject and students do not find anything interesting in it. This impression about Mathematics can be reversed with the help of recreational activities in Mathematics. The present study tries to find out the effectiveness of integrating riddles in teaching mathematics among eighth standard students. Two equivalent group experimental-designs are employed for this study. The investigator has chosen 40 eighth standard students for the study. According to the scoring of pre-test, 20 students were chosen as control group and 20 students were chosen as experimental group. Finally the investigator concludes; (a) There is a significant difference between the means of students thought through conventional method and puzzles and riddles way of learning group. (b) There is a significant difference between the means of the Post-Test scores of control group and experimental group students with respect to the knowledge, understanding and application objectives.
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International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Title Page in APA style with Running HeadAPA style AbstractInt.docx
Title Page in APA style with Running Head
APA style Abstract
Introduction
(Enter information in a bulleted format. Each bullet should be followed by 2-4 sentences.)
*NOTE: This first table is an example. You will need to delete the information in the table then, enter your question & data.
Results
Question: What is the relationship between academic interest and academic performance?
Allen & Robbins (2010)
Background Theory/Past Research Quote: Page 24
“When applied to students in postsecondary education, Holland’s theory suggests that students are more likely to be satisfied and succeed when their interests are congruent with their academic environments (Smart, Feldman, & Ethington, 2000).”
“In another study, first-year GPA and a measure of interest–major congruence both had relatively large effects on whether students changed major, suggesting that students with greater interest–major congruence are (a) more satisfied with their academic program and (b) more likely to graduate in a timely fashion due to not changing majors (Allen & Robbins, 2008).”
Background Theory/Past Research: Page 24
Students are more likely to do well in college when their interests are related to their major and academic environment (Smart, Feldman, & Ethington as cited in Allen & Robbins, 2010). Students whose major and interests are closely related are likely to graduate more quickly because of their low likelihood of changing majors (Allen & Robbins as cited in Allen & Robbins, 2008).
Research Hypothesis Quote:
Page 25
“Thus, we hypothesize that higher interest–major congruence has a positive effect on first-year academic performance. By virtue of having greater satisfaction with students’ major, Holland’s theory also suggests that greater interest–major congruence will lead to students satisfying their degree requirements earlier.”
“Thus, our second hypothesis is that interest–major congruence has a positive direct affect on timely degree attainment (beyond the effects of first-year academic performance).”
Research Hypothesis:
Page 25
Students with higher interest-major congruence will do better in their first year at college. Also, Allen & Robbins hypothesized that students with higher interest-major congruence will also earn their degree faster.
Methods Quote:
Page 26-8
“Furthermore, 3,860 (3,072 four-year and 788 two-year) of these students began as full-time students with expectations of earning at least a bachelor’s (4-year) or certificate (2-year) degree. This is the sample of students on which this study is based.”
“To be included in the study sample, students must (a) have taken the ACT tests of educational achievement and completed the Unisex Edition of the ACT Interest Inventory (UNIACT; ACT, 1995) when registering for the ACT;”
“The edition of UNIACT used in this study has 90 items (15 per scale) that describe work-relevant activities that are familiar to people either through participation or observation. For each item, students indicate wheth ...
12Insert Title HereInsert Your Name HereInsert
1
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations if the models are statistically significant. Delete instructions and examples highlighted in yellow before submitting this assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1:There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, ...
12Insert Title HereInsert Your Name HereInsert
1
2
Insert Title Here
Insert Your Name Here
Insert University Here
Course Name Here
Instructor Name
Date
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations if the models are statistically significant. Delete instructions and examples highlighted in yellow before submitting this assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1:There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, ...
STRUCTURAL EQUATION MODEL (SEM)
ABSTRACT : This paper critically examined a broad view of Structural Equation Model (SEM) with a view
of pointing out direction on how researchers can employ this model to future researches, with specific focus on
several traditional multivariate procedures like factor analysis, discriminant analysis, path analysis. This study
employed a descriptive survey and historical research design. Data was computed viaDescriptive Statistics,
Correlation Coefficient, Reliability. The study concluded that Novice researchers must take care of assumptions
and concepts of Structure Equation Modeling, while building a model to check the proposed hypothesis. SEM is
more or less an evolving technique in the research, which is expanding to new fields. Moreover, it is providing
new insights to researchers for conducting longitudinal investigations.
.
An Empirical Study on the Change of Consumption Level of Chinese Residents
With the rapid development of Chinese economy since the reform and opening up, people's living standards have been improved, and people's consumption level has been gradually improved. Consumption plays an important role in stimulating economic growth. At present, China needs to adjust its economic structure and optimize its industrial structure. Therefore, it is very important to analyze the factors that affect the consumption level of Chinese residents and study the main factors for promoting the healthy and sustainable development of Chinese economy. Therefore, based on the statistical data from 1995 to 2018, this paper collects the variable data that affects the consumption level of residents, such as the freight volume of infrastructure railway and highway, the per capita disposable income of national residents, ordinary college students, the consumer price index of residents, the average real wage index and the gross domestic product. And through the establishment of multiple linear regression model and the stepwise regression, the paper also finds out the main factors influencing the consumption level of residents. Using R language and analyzing the results of the research, we can draw the conclusion that the national per capita disposable income, ordinary college students and consumer price index and GDP are the main factors that affect the consumption level of Chine.
Data Analysis and Interpretation.pptx
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Econometrics _1.pptx
The aim of this course is to equip the students with the necessary skills, including both the acquisition of habits of thought and knowledge of the techniques of modern econometrics.
The course is application oriented.
The course also aims to provide students with the ability to use appropriate software in an effective manner.
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An Empirical Study on the Change of Consumption Level of Chinese Residents
An Empirical Study on the Change of Consumption Level of Chinese Residents
Analysis of Demand, Cost and Income of a Private Education Institution - A St...
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Latino Buying Power - May 2024 Presentation for Latino Caucus
Unlock the potential of Latino Buying Power with this in-depth SlideShare presentation. Explore how the Latino consumer market is transforming the American economy, driven by their significant buying power, entrepreneurial contributions, and growing influence across various sectors.
**Key Sections Covered:**
1. **Economic Impact:** Understand the profound economic impact of Latino consumers on the U.S. economy. Discover how their increasing purchasing power is fueling growth in key industries and contributing to national economic prosperity.
2. **Buying Power:** Dive into detailed analyses of Latino buying power, including its growth trends, key drivers, and projections for the future. Learn how this influential group’s spending habits are shaping market dynamics and creating opportunities for businesses.
3. **Entrepreneurial Contributions:** Explore the entrepreneurial spirit within the Latino community. Examine how Latino-owned businesses are thriving and contributing to job creation, innovation, and economic diversification.
4. **Workforce Statistics:** Gain insights into the role of Latino workers in the American labor market. Review statistics on employment rates, occupational distribution, and the economic contributions of Latino professionals across various industries.
5. **Media Consumption:** Understand the media consumption habits of Latino audiences. Discover their preferences for digital platforms, television, radio, and social media. Learn how these consumption patterns are influencing advertising strategies and media content.
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This SlideShare provides valuable insights for marketers, business owners, policymakers, and anyone interested in the economic influence of the Latino community. By understanding the various facets of Latino buying power, you can effectively engage with this dynamic and growing market segment.
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USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
when will pi network coin be available on crypto exchange.
There is no set date for when Pi coins will enter the market.
However, the developers are working hard to get them released as soon as possible.
Once they are available, users will be able to exchange other cryptocurrencies for Pi coins on designated exchanges.
But for now the only way to sell your pi coins is through verified pi vendor.
Here is the telegram contact of my personal pi vendor
@Pi_vendor_247
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how to sell pi coins in all Africa Countries.
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
what is a pi whale and how to access one.
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
What price will pi network be listed on exchanges
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
US Economic Outlook - Being Decided - M Capital Group August 2021.pdf
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
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While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
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Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
how to swap pi coins to foreign currency withdrawable.
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
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It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
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what is the future of Pi Network currency.
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
一比一原版Birmingham毕业证伯明翰大学|学院毕业证成绩单如何办理
Birmingham毕业证原版定制【微信：176555708】【伯明翰大学|学院毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆
【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
学历顾问：微信：176555708
一比一原版UOL毕业证利物浦大学毕业证成绩单如何办理
UOL毕业证原版定制【微信：176555708】【利物浦大学毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆
【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
学历顾问：微信：176555708
how to sell pi coins on Bitmart crypto exchange
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
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- 2. INTRODUCTION The purpose of this project is to prove the Bivariate regression model with the help of 2 variables. Here, Independent Variable- Pocket money of college students Dependent Variable- amount spent on stationary These factors will assist in studying school and college students’ the relation between the amount spent by them on stationary items and the amount of money they get as pocket money.
- 3. OBJECTIVE To find the relationship between two variables based on the collected data of college going students. The population for the data collection is school and college going students with the sample being students of amity university noida and various . The main objective is to find the amount of their pocket moneys which is spent on purchasing stationary. To find the equation for the best possible straight line that defines the relationship between two variables based on the collected data sets.
- 4. METHODOLOGY ● As for the data collection, primary data will be collected from 25 individuals by using google forms survey. ● A total of 2 questions were asked to perform the assessment of saving behaviour of college students. ● To perform the assessment, I’ll be using Excel and Stata.
- 5. HYPOTHESIS Null Hypothesis (H0): There is no significant relationship between the amount of pocket money one gets and how much he/she spends on stationary. Alternative Hypothesis (H1): There is a significant relationship between the amount of pocket money one gets and how much he/she spends on stationary.
- 8. Data
- 9. T-TEST ● FOR β1, ● Tcalculated= -0.76 ● Tcritical= 1.711 ● Tcalculated < Tcritical ● Therefore, the null hypothesis is ACCEPTED ● FOR β1, ● Tcalculated= 5.94 ● Tcritical= 1.711 ● Tcalculated > Tcritical ● Therefore, the null hypothesis is REJECTED
- 10. INTERPRETATION In the above case, calculated t is more than critical t. Therefore we reject the null hypothesis and accept the alternative hypothesis. This proves that there is a significant relationship between both.
- 11. REFERENCES 1. Gujarathi, D. M. (2022). Gujarati: Basic Econometrics. McGraw-hill. 2. Wainwright, K. (2005). Fundamental methods of mathematical economics. Boston, Mass. McGraw-Hill/Irwin. 3. Johnston, J., & DiNardo, J. (1963). Econometric methods.