2x-5y=4 and 7x-3y=4 using addition method
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Determine whether the following equation defines y as a function of x:
x2 + y2 = 16A. Y is a function of xB. X is not a function of yC. X is a function of x.D. Y is not a function of x
Determine whether the following equation defines y as a function of x:
x2 + y2 = 16A. Y is a function of xB. X is not a function of yC. X is a function of x.D. Y is not a function of x
Excelsior College PBH 592 Histogram in SPSS Paper
In this exercise, refer to the Framingham dataset and select a continuous variable. Select a variable and create a histogr ...
Excelsior College PBH 592 Histogram in SPSS Paper
In this exercise, refer to the Framingham dataset and select a continuous variable. Select a variable and create a histogram using the "Histogram in SPSS" video tutorial.
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I need help with answering the questions. On the third tab is where the answers are input. Some questions have a drop down ...
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MATH 110 American Public University Wk 7 Conic Shapes in The Real World Discussion
1: Conics are Everywhere!This is an opportunity to explore occurrences of conic sections in the world around us. Click on ...
MATH 110 American Public University Wk 7 Conic Shapes in The Real World Discussion
1: Conics are Everywhere!This is an opportunity to explore occurrences of conic sections in the world around us. Click on "View Full Description" below for the directions.
Conic shapes in the real world
MATH 114 Liberty University Causes of Death in 1980 and 2016 Questions
Topic – Causes of Death in 1980 and 2016According to the 1980 Census, the United States population was approximately 226 ...
MATH 114 Liberty University Causes of Death in 1980 and 2016 Questions
Topic – Causes of Death in 1980 and 2016According to the 1980 Census, the United States population was approximately 226,540,000 in 1980. It grew to approximately 323,120,000 at the beginning of 2016. Using Census data for 1980 and estimates derived from mortality data for 2016, we arrive at the population estimates given in the table below: undefined Year Total Population Ages 15–24 Ages 25–44 Ages 45–64 1980 226,540,000 42,475,000 62,707,000 44,497,000 2016 323,120,000 43,500,000 85,150,000 84,300,000 undefinedThe National Center for Health Statistics published a document entitled “Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities” that includes a table listing the leading causes of death in 1980 by age bracket. The CDC further produced a National Vital Statistics Reports that provided similar information for the year 2016. Under the Project Instructions link in Blackboard, you’ll find Discussion Board Forum 2: Data, a spreadsheet showing the leading causes of death in both 1980 and 2016 for these 3 age categories. Each of the first 3 questions has both a computational part and a discussion part. To get full credit for each of the discussion parts, please cite a reference to support your claims. This should not be an excessively difficult task: you can easily find information online for most of the illnesses or other causes listed in the report. All you need to do is provide the website you used (though other resources are also permitted if you prefer to use one of those). undefined1. Assuming that the population numbers in the above table are relatively accurate, use the Discussion Board Forum 2: Data spreadsheet to compute the deaths per 1000 people for each age group in both 1980 and 2016. Deaths per 1000 people is computed using the formula Deaths per 1000 = (# of deaths) / (total population) Do not round your answer to the nearest whole number, provide at least 2 decimal places (but no more than 4). Give these 6 values (e.g. deaths per 1000 people for ages 15–24 in 1980) and then cite a reference to discuss what might account for the changes between the deaths per 1000 in 1 of these 3 age categories between 1980 and 2016. Your discussion should be at least 40 words. 2. Besides the changes in the overall death rate in the past 3 decades, the leading causes of death vary somewhat between 1980 and 2016. Choose 1 of the 3 age ranges and select 1 cause of death from the Discussion Board Forum 2: Data spreadsheet that strikes you as noteworthy and that appears in both the 1980 and 2016 lists. For the cause of death that you selected, compute the number of deaths per 1000 in both 1980 and 2016 for your chosen age group. Do not round your answer to the nearest whole number, provide at least 2 decimal places. Cite a reference to discuss the possible reasons for any changes in the rates over this period. Your discussion should be at least 40 words. 3. Not only do the leading causes of death vary across time, they vary significantly for different age ranges. Looking only at the 2016 data, choose a cause of death that appears in both the 25–44 and 45–64 age categories and compute the number of deaths per 1000 people for both age categories. Do not round your answer to the nearest whole number, provide at least 2 decimal places. Cite a reference to discuss a possible reason for any differences in these values as people advance in age. Your discussion should be at least 40 words. 4. Contemplating causes of death might strike some people as unpleasant or even morbid. However, the Bible encourages us to give some thought to the fact of our own mortality. Ecclesiastes 7:2–4 says: “It is better to go to the house of mourning than to go to the house of feasting, for this is the end of all mankind, and the living will lay it to heart. Sorrow is better than laughter, for by sadness of face the heart is made glad. The heart of the wise is in the house of mourning, but the heart of fools is in the house of mirth.” It is interesting to consider why the author of Ecclesiastes encourages the wise to go to the house of mourning and the living to lay the end of all mankind to heart. What value might there be in thinking about the, admittedly uncomfortable, subject of the end of all mankind? What comes to your mind when you consider this topic? Please respond with at least 80 words.
Week 5 Statistical Significance & Meaningfulness on Sample Statements Paper
Part of your task as a scholar-practitioner is to act as a
critical consumer of research and ask informed ques ...
Week 5 Statistical Significance & Meaningfulness on Sample Statements Paper
Part of your task as a scholar-practitioner is to act as a
critical consumer of research and ask informed questions of published
material. Sometimes, claims are made that do not match the results of
the analysis. Unfortunately, this is why statistics is sometimes
unfairly associated with telling lies. These misalignments might not be
solely attributable to statistical nonsense, but also “user error.” One
of the greatest areas of user error is within the practice of hypothesis
testing and interpreting statistical significance. As you continue to
consume research, be sure and read everything with a critical eye and
call out statements that do not match the results.
For this Assignment, you will examine statistical significance and meaningfulness based on sample statements.To prepare for this Assignment:Review the Week 5 Scenarios found in this week’s Learning Resources and select two of the four scenarios for this Assignment. For additional support, review the Skill Builder: Evaluating P Values and the Skill Builder: Statistical Power,
which you can find by navigating back to your Blackboard Course Home
Page. From there, locate the Skill Builder link in the left navigation
pane. For this Assignment:Critically evaluate the two scenarios you selected based upon the following points:Critically evaluate the sample size.Critically evaluate the statements for meaningfulness.Critically evaluate the statements for statistical significance.Based on your evaluation, provide an explanation of the implications for social change.Use proper APA format and citations, and referencing.Week 5 Scenarios:1.The p-value was slightly above conventional threshold, but was described as “rapidly approaching significance” (i.e., p=.06). An independent samples t test was used to determine whether student satisfaction levels in a quantitative reasoning course differed between the traditional classroom and on-line environments.The samples consisted of students in four face-to-face classes at a traditional state university (n=65) and four online classes offered at the same university (n=69). Students reported their level of satisfaction on a five-point scale, with higher values indicating higher levels of satisfaction.Since the study was exploratory in nature, levels of significance were relaxed to the .10 level. The test was significant t(132) = 1.8, p= .074, wherein students in the face-to-face class reported lower levels of satisfaction (M= 3.39, SD= 1.8)than did those in the online sections (M= 3.89, SD= 1.4).We therefore conclude that on average, students in online quantitative reasoning classes have higher levels of satisfaction.The results of this study are significant because they provide educators with evidence of what medium works better in producing quantitatively knowledgeable practitioners.2.A results report that does not find any effect and also has small sample size (possibly no effect detected due to lack of power). A one-way analysis of variance was used to test whether a relationship exists between educational attainment and race. The dependent variable of education was measured as number of years of education completed. The race factor had three attributes of European American (n=36), African American (n=23) and Hispanic (n=18). Descriptive statistics indicate that on average, European Americans have higher levels of education (M=16.4, SD=4.6), with African Americans slightly trailing (M= 15.5, SD=6.8) and Hispanics having on average lower levels of educational attainment (M=13.3, SD=6.1). The ANOVA was not significant F(2,74) = 1.789, p= .175, indicating there are no differences in educational attainment across these three races in the population.The results of this study are significant because they shed light on the current social conversation about inequality. 3.Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?An independent samples t test was conducted to determine whether differences exist between men and women on cultural competency scores. The samples consisted of 663 women and 650 men taken from a convenience sample of public, private,and non-profit organizations. Each participant was administered an instrument that measured his or her current levels of cultural competency. The © 2016 Laureate Education, Inc. Page 2of 2cultural competency score ranges from 0 to 10,with higher scores indicating higher levels of cultural competency. The descriptive statistics indicate women have higher levels of cultural competency (M= 9.2, SD= 3.2) than men (M= 8.9, SD=2.1). The results were significant t(1311) = 2.0, p<.05, indicating that women are more culturally competent than are men. These results tell us that gender-specific interventions targeted toward men may assist in bolstering cultural competency. 4.A study has results that seem fine, but there is no clear association to social change. What is missing? A correlation test was conducted to determine whether a relationship exists between level of income and job satisfaction. The sample consisted of 432 employees equally represented across public, private,and non-profit sectors. The results of the test demonstrate a strong positive correlation between the two variables,r=.87, p<.01, showing that as level of income increases, job satisfaction increases as well.
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Determine whether the following equation defines y as a function of x:
x2 + y2 = 16A. Y is a function of xB. X is not a function of yC. X is a function of x.D. Y is not a function of x
Determine whether the following equation defines y as a function of x:
x2 + y2 = 16A. Y is a function of xB. X is not a function of yC. X is a function of x.D. Y is not a function of x
Excelsior College PBH 592 Histogram in SPSS Paper
In this exercise, refer to the Framingham dataset and select a continuous variable. Select a variable and create a histogr ...
Excelsior College PBH 592 Histogram in SPSS Paper
In this exercise, refer to the Framingham dataset and select a continuous variable. Select a variable and create a histogram using the "Histogram in SPSS" video tutorial.
QMB3200 St. Petersburg Hypothesis Testing for the Population Mean Report
I need help with answering the questions. On the third tab is where the answers are input. Some questions have a drop down ...
QMB3200 St. Petersburg Hypothesis Testing for the Population Mean Report
I need help with answering the questions. On the third tab is where the answers are input. Some questions have a drop down menu to choose from!!Second tab is the data, and first tab is the instructions. QMB3200 Quantitative Methods for Business
MATH 110 American Public University Wk 7 Conic Shapes in The Real World Discussion
1: Conics are Everywhere!This is an opportunity to explore occurrences of conic sections in the world around us. Click on ...
MATH 110 American Public University Wk 7 Conic Shapes in The Real World Discussion
1: Conics are Everywhere!This is an opportunity to explore occurrences of conic sections in the world around us. Click on "View Full Description" below for the directions.
Conic shapes in the real world
MATH 114 Liberty University Causes of Death in 1980 and 2016 Questions
Topic – Causes of Death in 1980 and 2016According to the 1980 Census, the United States population was approximately 226 ...
MATH 114 Liberty University Causes of Death in 1980 and 2016 Questions
Topic – Causes of Death in 1980 and 2016According to the 1980 Census, the United States population was approximately 226,540,000 in 1980. It grew to approximately 323,120,000 at the beginning of 2016. Using Census data for 1980 and estimates derived from mortality data for 2016, we arrive at the population estimates given in the table below: undefined Year Total Population Ages 15–24 Ages 25–44 Ages 45–64 1980 226,540,000 42,475,000 62,707,000 44,497,000 2016 323,120,000 43,500,000 85,150,000 84,300,000 undefinedThe National Center for Health Statistics published a document entitled “Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities” that includes a table listing the leading causes of death in 1980 by age bracket. The CDC further produced a National Vital Statistics Reports that provided similar information for the year 2016. Under the Project Instructions link in Blackboard, you’ll find Discussion Board Forum 2: Data, a spreadsheet showing the leading causes of death in both 1980 and 2016 for these 3 age categories. Each of the first 3 questions has both a computational part and a discussion part. To get full credit for each of the discussion parts, please cite a reference to support your claims. This should not be an excessively difficult task: you can easily find information online for most of the illnesses or other causes listed in the report. All you need to do is provide the website you used (though other resources are also permitted if you prefer to use one of those). undefined1. Assuming that the population numbers in the above table are relatively accurate, use the Discussion Board Forum 2: Data spreadsheet to compute the deaths per 1000 people for each age group in both 1980 and 2016. Deaths per 1000 people is computed using the formula Deaths per 1000 = (# of deaths) / (total population) Do not round your answer to the nearest whole number, provide at least 2 decimal places (but no more than 4). Give these 6 values (e.g. deaths per 1000 people for ages 15–24 in 1980) and then cite a reference to discuss what might account for the changes between the deaths per 1000 in 1 of these 3 age categories between 1980 and 2016. Your discussion should be at least 40 words. 2. Besides the changes in the overall death rate in the past 3 decades, the leading causes of death vary somewhat between 1980 and 2016. Choose 1 of the 3 age ranges and select 1 cause of death from the Discussion Board Forum 2: Data spreadsheet that strikes you as noteworthy and that appears in both the 1980 and 2016 lists. For the cause of death that you selected, compute the number of deaths per 1000 in both 1980 and 2016 for your chosen age group. Do not round your answer to the nearest whole number, provide at least 2 decimal places. Cite a reference to discuss the possible reasons for any changes in the rates over this period. Your discussion should be at least 40 words. 3. Not only do the leading causes of death vary across time, they vary significantly for different age ranges. Looking only at the 2016 data, choose a cause of death that appears in both the 25–44 and 45–64 age categories and compute the number of deaths per 1000 people for both age categories. Do not round your answer to the nearest whole number, provide at least 2 decimal places. Cite a reference to discuss a possible reason for any differences in these values as people advance in age. Your discussion should be at least 40 words. 4. Contemplating causes of death might strike some people as unpleasant or even morbid. However, the Bible encourages us to give some thought to the fact of our own mortality. Ecclesiastes 7:2–4 says: “It is better to go to the house of mourning than to go to the house of feasting, for this is the end of all mankind, and the living will lay it to heart. Sorrow is better than laughter, for by sadness of face the heart is made glad. The heart of the wise is in the house of mourning, but the heart of fools is in the house of mirth.” It is interesting to consider why the author of Ecclesiastes encourages the wise to go to the house of mourning and the living to lay the end of all mankind to heart. What value might there be in thinking about the, admittedly uncomfortable, subject of the end of all mankind? What comes to your mind when you consider this topic? Please respond with at least 80 words.
Week 5 Statistical Significance & Meaningfulness on Sample Statements Paper
Part of your task as a scholar-practitioner is to act as a
critical consumer of research and ask informed ques ...
Week 5 Statistical Significance & Meaningfulness on Sample Statements Paper
Part of your task as a scholar-practitioner is to act as a
critical consumer of research and ask informed questions of published
material. Sometimes, claims are made that do not match the results of
the analysis. Unfortunately, this is why statistics is sometimes
unfairly associated with telling lies. These misalignments might not be
solely attributable to statistical nonsense, but also “user error.” One
of the greatest areas of user error is within the practice of hypothesis
testing and interpreting statistical significance. As you continue to
consume research, be sure and read everything with a critical eye and
call out statements that do not match the results.
For this Assignment, you will examine statistical significance and meaningfulness based on sample statements.To prepare for this Assignment:Review the Week 5 Scenarios found in this week’s Learning Resources and select two of the four scenarios for this Assignment. For additional support, review the Skill Builder: Evaluating P Values and the Skill Builder: Statistical Power,
which you can find by navigating back to your Blackboard Course Home
Page. From there, locate the Skill Builder link in the left navigation
pane. For this Assignment:Critically evaluate the two scenarios you selected based upon the following points:Critically evaluate the sample size.Critically evaluate the statements for meaningfulness.Critically evaluate the statements for statistical significance.Based on your evaluation, provide an explanation of the implications for social change.Use proper APA format and citations, and referencing.Week 5 Scenarios:1.The p-value was slightly above conventional threshold, but was described as “rapidly approaching significance” (i.e., p=.06). An independent samples t test was used to determine whether student satisfaction levels in a quantitative reasoning course differed between the traditional classroom and on-line environments.The samples consisted of students in four face-to-face classes at a traditional state university (n=65) and four online classes offered at the same university (n=69). Students reported their level of satisfaction on a five-point scale, with higher values indicating higher levels of satisfaction.Since the study was exploratory in nature, levels of significance were relaxed to the .10 level. The test was significant t(132) = 1.8, p= .074, wherein students in the face-to-face class reported lower levels of satisfaction (M= 3.39, SD= 1.8)than did those in the online sections (M= 3.89, SD= 1.4).We therefore conclude that on average, students in online quantitative reasoning classes have higher levels of satisfaction.The results of this study are significant because they provide educators with evidence of what medium works better in producing quantitatively knowledgeable practitioners.2.A results report that does not find any effect and also has small sample size (possibly no effect detected due to lack of power). A one-way analysis of variance was used to test whether a relationship exists between educational attainment and race. The dependent variable of education was measured as number of years of education completed. The race factor had three attributes of European American (n=36), African American (n=23) and Hispanic (n=18). Descriptive statistics indicate that on average, European Americans have higher levels of education (M=16.4, SD=4.6), with African Americans slightly trailing (M= 15.5, SD=6.8) and Hispanics having on average lower levels of educational attainment (M=13.3, SD=6.1). The ANOVA was not significant F(2,74) = 1.789, p= .175, indicating there are no differences in educational attainment across these three races in the population.The results of this study are significant because they shed light on the current social conversation about inequality. 3.Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?An independent samples t test was conducted to determine whether differences exist between men and women on cultural competency scores. The samples consisted of 663 women and 650 men taken from a convenience sample of public, private,and non-profit organizations. Each participant was administered an instrument that measured his or her current levels of cultural competency. The © 2016 Laureate Education, Inc. Page 2of 2cultural competency score ranges from 0 to 10,with higher scores indicating higher levels of cultural competency. The descriptive statistics indicate women have higher levels of cultural competency (M= 9.2, SD= 3.2) than men (M= 8.9, SD=2.1). The results were significant t(1311) = 2.0, p<.05, indicating that women are more culturally competent than are men. These results tell us that gender-specific interventions targeted toward men may assist in bolstering cultural competency. 4.A study has results that seem fine, but there is no clear association to social change. What is missing? A correlation test was conducted to determine whether a relationship exists between level of income and job satisfaction. The sample consisted of 432 employees equally represented across public, private,and non-profit sectors. The results of the test demonstrate a strong positive correlation between the two variables,r=.87, p<.01, showing that as level of income increases, job satisfaction increases as well.
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