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write my assignment 10284

Prepare answers to the following cases from this week’s reading.

  • Case 16.1: Specific Performance on page 278
  • Case 18.7: Goods or Service on page 313

Your responses should be well-rounded and analytical, and should not just provide a conclusion or an opinion without explaining the reason for the choice.

For full credit, you need to use the material from the week’s lectures, text, and/or discussions when responding to the questions. It is important that you incorporate the question into your response (i.e., restate the question in your introduction) and explain the legal principle(s) or concept(s) from the text that underlies your judgment.

For each question you should provide at least one reference in APA format (in-text citations and references as described in detail in the Syllabus). Each answer should be double spaced in 12-point font, and your response to each question should be between 300 and 350 words in length.

Submit this assignment as a single Word document covering both cases.

 

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SSA Expenditure approach

All expenditure incurred by individuals during 1 year . “In economics, most things produced are produced for sale and then sold. Therefore, measuring the total expenditure of money used to buy things is a way of measuring production. This is known as the expenditure method of calculating GDP. Note that if you knit yourself a sweater, it is production but does not get counted as GDP because it is never sold. Sweater-knitting is a small part of the economy, but if one counts some major activities such as child-rearing (generally unpaid) as production, GDP ceases to be an accurate indicator of production. Similarly, if there is a long-term shift from non-market provision of services (for example cooking, cleaning, child rearing, do-it yourself repairs) to market provision of services, then this trend toward increased market provision of services may mask a dramatic decrease in actual domestic production, resulting in overly optimistic and inflated reported GDP. This is particularly a problem for economies which have shifted from production economies to service economies.Components of GDP by expenditure[edit]Components of U.S. GDPGDP (Y) is a sum of Consumption (C), Investment (I), Government Spending (G) and Net Exports (X – M).Y = C + I + G + (X − M)Here is a description of each GDP component:C (consumption) is normally the largest GDP component in the economy, consisting of private (household final consumption expenditure) in the economy. These personal expenditures fall under one of the following categories: durable goods, non-durable goods, and services. Examples include food, rent, jewelry, gasoline, and medical expenses but does not include the purchase of new housing.I (investment) includes, for instance, business investment in equipment, but does not include exchanges of existing assets. Examples include construction of a new mine, purchase of software, or purchase of machinery and equipment for a factory. Spending by households (not government) on new houses is also included in Investment. In contrast to its colloquial meaning, ‘Investment’ in GDP does not mean purchases of financial products. Buying financial products is classed as ‘saving’, as opposed to investment. This avoids double-counting: if one buys shares in a company, and the company uses the money received to buy plant, equipment, etc., the amount will be counted toward GDP when the company spends the money on those things; to also count it when one gives it to the company would be to count two times an amount that only corresponds to one group of products. Buying bonds or stocks is a swapping of deeds, a transfer of claims on future production, not directly an expenditure on products.G (government spending) is the sum of government expenditures on final goods and services. It includes salaries of public servants, purchase of weapons for the military and any investment expenditure by a government. It does not include any transfer payments, such as social security or unemployment benefits.X (exports) represents gross exports. GDP captures the amount a country produces, including goods and services produced for other nations’ consumption, therefore exports are added.M (imports) represents gross imports. Imports are subtracted since imported goods will be included in the terms G, I, or C, and must be deducted to avoid counting foreign supply as domestic.A fully equivalent definition is that GDP (Y) is the sum of final consumption expenditure (FCE), gross capital formation (GCF), and net exports (X – M).Y = FCE + GCF+ (X − M)FCE can then be further broken down by three sectors (households, governments and non-profit institutions serving households) and GCF by five sectors (non-financial corporations, financial corporations, households, governments and non-profit institutions serving households). The advantage of this second definition is that expenditure is systematically broken down, firstly, by type of final use (final consumption or capital formation) and, secondly, by sectors making the expenditure, whereas the first definition partly follows a mixed delimitation concept by type of final use and sector.Note that C, G, and I are expenditures on final goods and services; expenditures on intermediate goods and services do not count. (Intermediate goods and services are those used by businesses to produce other goods and services within the accounting year.[9] )According to the U.S. Bureau of Economic Analysis, which is responsible for calculating the national accounts in the United States, “In general, the source data for the expenditures components are considered more reliable than those for the income components [see income method, below].”[10]Examples of GDP component variables[edit]C, I, G, and NX(net exports): If a person spends money to renovate a hotel to increase occupancy rates, the spending represents private investment, but if he buys shares in a consortium to execute the renovation, it is saving. The former is included when measuring GDP (in I), the latter is not. However, when the consortium conducted its own expenditure on renovation, that expenditure would be included in GDP.If a hotel is a private home, spending for renovation would be measured as consumption, but if a government agency converts the hotel into an office for civil servants, the spending would be included in the public sector spending, or G.If the renovation involves the purchase of a chandelier from abroad, that spending would be counted as C, G, or I (depending on whether a private individual, the government, or a business is doing the renovation), but then counted again as an import and subtracted from the GDP so that GDP counts only goods produced within the country.If a domestic producer is paid to make the chandelier for a foreign hotel, the payment would not be counted as C, G, or I, but would be counted as an export.GDP real growth rates for 2010.A “production boundary” delimits what will be counted as GDP.”One of the fundamental questions that must be addressed in preparing the national economic accounts is how to define the production boundary–that is, what parts of the myriad human activities are to be included in or excluded from the measure of the economic production.”[11]All output for market is at least in theory included within the boundary. Market output is defined as that which is sold for “economically significant” prices; economically significant prices are “prices which have a significant influence on the amounts producers are willing to supply and purchasers wish to buy.”[12] An exception is that illegal goods and services are often excluded even if they are sold at economically significant prices (Australia and the United States exclude them).This leaves non-market output. It is partly excluded and partly included. First, “natural processes without human involvement or direction” are excluded.[13] Also, there must be a person or institution that owns or is entitled to compensation for the product. An example of what is included and excluded by these criteria is given by the United States’ national accounts agency: “the growth of trees in an uncultivated forest is not included in production, but the harvesting of the trees from that forest is included.”[14]Within the limits so far described, the boundary is further constricted by “functional considerations.”[15] The Australian Bureau for Statistics explains this: “The national accounts are primarily constructed to assist governments and others to make market-based macroeconomic policy decisions, including analysis of markets and factors affecting market performance, such as inflation and unemployment.” Consequently, production that is, according to them, “relatively independent and isolated from markets,” or “difficult to value in an economically meaningful way” [i.e., difficult to put a price on] is excluded.[16] Thus excluded are services provided by people to members of their own families free of charge, such as child rearing, meal preparation, cleaning, transportation, entertainment of family members, emotional support, care of the elderly.[17] Most other production for own (or one’s family’s) use is also excluded, with two notable exceptions which are given in the list later in this section.Non-market outputs that are included within the boundary are listed below. Since, by definition, they do not have a market price, the compilers of GDP must impute a value to them, usually either the cost of the goods and services used to produce them, or the value of a similar item that is sold on the market.Goods and services provided by governments and non-profit organizations free of charge or for economically insignificant prices are included. The value of these goods and services is estimated as equal to their cost of production. This ignores the consumer surplus generated by an efficient and effective government supplied infrastructure. For example, government-provided clean water confers substantial benefits above its cost. Ironically, lack of such infrastructure which would result in higher water prices (and probably higher hospital and medication expenditures) would be reflected as a higher GDP. This may also cause a bias that mistakenly favors inefficient privatizations since some of the consumer surplus from privatized entities’ sale of goods and services are indeed reflected in GDP.[18] xGoods and services produced for own-use by businesses are attempted to be included. An example of this kind of production would be a machine constructed by an engineering firm for use in its own plant.Renovations and upkeep by an individual to a home that she owns and occupies are included. The value of the upkeep is estimated as the rent that she could charge for the home if she did not occupy it herself. This is the largest item of production for own use by an individual (as opposed to a business) that the compilers include in GDP.[18] If the measure uses historical or book prices for real estate, this will grossly underestimate the value of the rent in real estate markets which have experienced significant price increases (or economies with general inflation). Furthermore, depreciation schedules for houses often accelerate the accounted depreciation relative to actual depreciation (a well built house can be lived in for several hundred years – a very long time after it has been fully depreciated). In summary, this is likely to grossly underestimate the value of existing housing stock on consumers’ actual consumption or income.Agricultural production for consumption by oneself or one’s household is included.Services (such as chequeing-account maintenance and services to borrowers) provided by banks and other financial institutions without charge or for a fee that does not reflect their full value have a value imputed to them by the compilers and are included. The financial institutions provide these services by giving the customer a less advantageous interest rate than they would if the services were absent; the value imputed to these services by the compilers is the difference between the interest rate of the account with the services and the interest rate of a similar account that does not have the services. According to the United States Bureau for Economic Analysis, this is one of the largest imputed items in the GDP.[19]GDP vs GNI[edit]GDP can be contrasted with gross national product (GNP) or, as it is now known, gross national income (GNI). The difference is that GDP defines its scope according to location, while GNI defines its scope according to ownership. In a global context, world GDP and world GNI are, therefore, equivalent terms.GDP is product produced within a country’s borders; GNI is product produced by enterprises owned by a country’s citizens. The two would be the same if all of the productive enterprises in a country were owned by its own citizens, and those citizens did not own productive enterprises in any other countries. In practice, however, foreign ownership makes GDP and GNI non-identical. Production within a country’s borders, but by an enterprise owned by somebody outside the country, counts as part of its GDP but not its GNI; on the other hand, production by an enterprise located outside the country, but owned by one of its citizens, counts as part of its GNP but not its GDP.To take the United States as an example, the U.S.’s GNI is the value of output produced by American-owned firms, regardless of where the firms are located. Similarly, if a country becomes increasingly in debt, and spends large amounts of income servicing this debt this will be reflected in a decreased GNI but not a decreased GDP. Similarly, if a country sells off its resources to entities outside their country this will also be reflected over time in decreased GNI, but not decreased GDP. This would make the use of GDP more attractive for politicians in countries with increasing national debt and decreasing assets.Gross national income (GNI) equals GDP plus income receipts from the rest of the world minus income payments to the rest of the world.[20]In 1991, the United States switched from using GNP to using GDP as its primary measure of production.[21] The relationship between United States GDP and GNP is shown in table 1.7.5 of the National Income and Product Accounts.[22]International standards[edit]The international standard for measuring GDP is contained in the book System of National Accounts (1993), which was prepared by representatives of the International Monetary Fund, European Union, Organization for Economic Co-operation and Development, United Nations and World Bank. The publication is normally referred to as SNA93 to distinguish it from the previous edition published in 1968 (called SNA68) [23]SNA93 provides a set of rules and procedures for the measurement of national accounts. The standards are designed to be flexible, to allow for differences in local statistical needs and conditions.[icon]This section requires expansion. (August 2009)National measurement[edit]Within each country GDP is normally measured by a national government statistical agency, as private sector organizations normally do not have access to the information required (especially information on expenditure and production by governments).Main article: National agencies responsible for GDP measurementInterest rates[edit]Net interest expense is a transfer payment in all sectors except the financial sector. Net interest expenses in the financial sector are seen as production and value added and are added to GDP.Nominal GDP and adjustments to GDP[edit]The raw GDP figure as given by the equations above is called the nominal, historical, or current, GDP. When one compares GDP figures from one year to another, it is desirable to compensate for changes in the value of money – i.e., for the effects of inflation or deflation. To make it more meaningful for year-to-year comparisons, it may be multiplied by the ratio between the value of money in the year the GDP was measured and the value of money in a base year.For example, suppose a country’s GDP in 1990 was $100 million and its GDP in 2000 was $300 million. Suppose also that inflation had halved the value of its currency over that period. To meaningfully compare its GDP in 2000 to its GDP in 1990, we could multiply the GDP in 2000 by one-half, to make it relative to 1990 as a base year. The result would be that the GDP in 2000 equals $300 million × one-half = $150 million, in 1990 monetary terms. We would see that the country’s GDP had realistically increased 50 percent over that period, not 200 percent, as it might appear from the raw GDP data. The GDP adjusted for changes in money value in this way is called the real, or constant, GDP.The factor used to convert GDP from current to constant values in this way is called the GDP deflator. Unlike consumer price index, which measures inflation or deflation in the price of household consumer goods, the GDP deflator measures changes in the prices of all domestically produced goods and services in an economy including investment goods and government services, as well as household consumption goods.[24]Constant-GDP figures allow us to calculate a GDP growth rate, which indicates how much a country’s production has increased (or decreased, if the growth rate is negative) compared to the previous year.Real GDP growth rate for year n = [(Real GDP in year n) − (Real GDP in year n − 1)] / (Real GDP in year n − 1)Another thing that it may be desirable to account for is population growth. If a country’s GDP doubled over a certain period, but its population tripled, the increase in GDP may not mean that the standard of living increased for the country’s residents; the average person in the country is producing less than they were before. Per-capita GDP is a measure to account for population growth.Cross-border comparison and PPP[edit]The level of GDP in different countries may be compared by converting their value in national currency according to either the current currency exchange rate, or the purchasing power parity exchange rate.Current currency exchange rate is the exchange rate in the international foreign exchange market.Purchasing power parity exchange rate is the exchange rate based on the purchasing power parity (PPP) of a currency relative to a selected standard (usually the United States dollar). This is a comparative (and theoretical) exchange rate, the only way to directly realize this rate is to sell an entire CPI basket in one country, convert the cash at the currency market rate & then rebuy that same basket of goods in the other country (with the converted cash). Going from country to country, the distribution of prices within the basket will vary; typically, non-tradable purchases will consume a greater proportion of the basket’s total cost in the higher GDP country, per the Balassa-Samuelson effect.The ranking of countries may differ significantly based on which method is used.The current exchange rate method converts the value of goods and services using global currency exchange rates. The method can offer better indications of a country’s international purchasing power and relative economic strength. For instance, if 10% of GDP is being spent on buying hi-tech foreign arms, the number of weapons purchased is entirely governed by current exchange rates, since arms are a traded product bought on the international market. There is no meaningful ‘local’ price distinct from the international price for high technology goods.The purchasing power parity method accounts for the relative effective domestic purchasing power of the average producer or consumer within an economy. The method can provide a better indicator of the living standards of less developed countries, because it compensates for the weakness of local currencies in the international markets. For example, India ranks 10th by nominal GDP, but 3rd by PPP. The PPP method of GDP conversion is more relevant to non-traded goods and services.There is a clear pattern of the purchasing power parity method decreasing the disparity in GDP between high and low income (GDP) countries, as compared to the current exchange rate method. This finding is called the Penn effect.For more information, see Measures of national income and output.Per unit GDP[edit]GDP is an aggregate figure which does not consider differing sizes of nations. Therefore, GDP can be stated as GDP per capita (per person) in which total GDP is divided by the resident population on a given date, GDP per citizen where total GDP is divided by the numbers of citizens residing in the country on a given date, and less commonly GDP per unit of a resource input, such as GDP per GJ of energy or Gross domestic product per barrel. GDP per citizen in the above case is pretty similar to GDP per capita in most nations, however, in nations with very high proportions of temporary foreign workers like in Persian Gulf nations, the two figures can be vastly different.Standard of living and GDP[edit]GDP per capita is not a measurement of the standard of living in an economy; however, it is often used as such an indicator, on the rationale that all citizens would benefit from their country’s increased economic production. Similarly, GDP per capita is not a measure of personal income. GDP may increase while real incomes for the majority decline. The major advantage of GDP per capita as an indicator of standard of living is that it is measured frequently, widely, and consistently. It is measured frequently in that most countries provide information on GDP on a quarterly basis, allowing trends to be seen quickly. It is measured widely in that some measure of GDP is available for almost every country in the world, allowing inter-country comparisons. It is measured consistently in that the technical definition of GDP is relatively consistent among countries.The major disadvantage is that it is not a measure of standard of living. GDP is intended to be a measure of total national economic activity—a separate concept.The argument for using GDP as a standard-of-living proxy is not that it is a good indicator of the absolute level of standard of living, but that living standards tend to move with per-capita GDP, so that changes in living standards are readily detected through changes in GDP.Externalities[edit]GDP is widely used by economists to gauge economic recession and recovery and an economy’s general monetary ability to address externalities. It is not meant to measure externalities. It serves as a general metric for a nominal monetary standard of living and is not adjusted for costs of living within a region. GDP is a neutral measure which merely shows an economy’s general ability to pay for externalities such as social and environmental concerns.[25] Examples of externalities include:Wealth distribution – GDP does not account for variances in incomes of various demographic groups. See income inequality metrics for discussion of a variety of inequality-based economic measures.Non-market transactions–GDP excludes activities that are not provided through the market, such as household production and volunteer or unpaid services. As a result, GDP is understated. Unpaid work conducted on Free and Open Source Software (such as GNU/Linux) contribute nothing to GDP, but it was estimated that it would have cost more than a billion US dollars for a commercial company to develop. Also, if Free and Open Source Software became identical to its proprietary software counterparts, and the nation producing the propriety software stops buying proprietary software and switches to Free and Open Source Software, then the GDP of this nation would reduce; however, there would be no reduction in economic production or standard of living. The work of New Zealand economist Marilyn Waring has highlighted that if a concerted attempt to factor in unpaid work were made, then it would in part undo the injustices of unpaid (and in some cases, slave) labour, and also provide the political transparency and accountability necessary for democracy.Underground economy–Official GDP estimates may not take into account the underground economy, in which transactions contributing to production, such as illegal trade and tax-avoiding activities, are unreported, causing GDP to be underestimated.Asset Value–GDP does take into account the value of all assets in an economy. This is akin to ignoring a company’s balance sheet, and judging it solely on the basis of its income statement.Non-monetary economy–GDP omits economies where no money comes into play at all, resulting in inaccurate or abnormally low GDP figures. For example, in countries with major business transactions occurring informally, portions of local economy are not easily registered. Bartering may be more prominent than the use of money, even extending to services (I helped you build your house ten years ago, so now you help me).GDP also ignores subsistence production.Quality improvements and inclusion of new products–By not adjusting for quality improvements and new products, GDP understates true economic growth. For instance, although computers today are less expensive and more powerful than computers from the past, GDP treats them as the same products by only accounting for the monetary value. The introduction of new products is also difficult to measure accurately and is not reflected in GDP despite the fact that it may increase the standard of living. For example, even the richest person from 1900 could not purchase standard products, such as antibiotics and cell phones, that an average consumer can buy today, since such modern conveniences did not exist back then.What is being produced–GDP counts work that produces no net change or that results from repairing harm. For example, rebuilding after a natural disaster or war may produce a considerable amount of economic activity and thus boost GDP. The economic value of health care is another classic example—it may raise GDP if many people are sick and they are receiving expensive treatment, but it is not a desirable situation. Alternative economic estimates, such as the standard of living or discretionary income per capita try to measure the human utility of economic activity. See uneconomic growth.

 

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write my assignment 7695

Now let us look at another activity centered on calculating the mean, median, and mode (measures of central tendency). In this exercise I would like each Learning Team to gather the number of miles on his/her car, the age of his/her car, and the approximate distance he/she drives to work (past/present). Record those results in the table below. Next, determine the mean, median, and mode for each column. Finally, have a group member serve as the spokesperson and post the group’s findings.

Miles on Odometer

Age of Car

Distance to Work

Person A

Person B

Person C

Person D

Person E

Person F

Class,

Complete the exercise above, responding to this post with your table/results.

Jaggia, S., Kelly, A. (2014). Essentials of Business Statistics. USA: McGraw-Hill Companies, Inc.

 

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write my assignment 31146

religious). Then, we hypothesize that, because women outlive men, and because women are typically more religious than men are, part of this age effect is actually due to sex. We run a second model in which we add a variable for sex:

Independent Variable                                      Model 1                       Model 2

Age (in years)                                                 0.03***                       0.03***

Sex (, )                                              —                                -0.93***

Constant                                                          4.23                             4.65

R-Squared                                                       0.04                            0.07

n                                                                      2912                            2912

Which of the following is the most appropriate interpretation of what is going on here?

a.) Sex clearly has a larger effect than age, so our hypothesis is supported.

b.) The value of R-Squared rises, so our hypothesis is supported.

c.) The effect of age does not change, so our hypothesis is not supported.

d.) The constant increases, so our hypothesis is not supported.

5.) We hypothetically observe that the higher one’s education, the happier one is. We hypothesize that this is actually because of income: people with higher education tend to make higher incomes, and it is these higher incomes, not education, that causes the higher happiness. Here are hypothetical models (using a dependent variable where at all happy, up to happy):

Independent Variable                                      Model 1                       Model 2

Education (in years)                                        0.35***                       ???

Income (in thousands of dollars)                     —                                0.03***

Constant                                                          0.50                             -2.50

R-Squared                                                       0.10                            0.15

n                                                                      1000                            1000

To support the hypothesis, what is the most likely number that would go in the place of the “???” in Model 2?

a.) .03

b.) .20**

c.) .35*

d.) .50***

6.) In Model 1, Independent Variable A has a statistically significant effect. In Model 2, we add Independent Variable B, which has a statistically significant effect, and the effect of Independent Variable A moves closer to zero and loses its statistical significance. What might we have here?

a.) an intervening relationship

b.) a dependent relationship

c.) an independent relationship

d.) a controlling relationship

7.)

a.) We are interested in explaining the number of hours per week that the CRMJ 321 students spend playing videogames during the school year (rvidsch). Perhaps, we think, this variable can be explained by some students’ political views! We use our political variables to predict videogame playing and end up with the following regression (Model 1):

. regress rvidsch abort deathpen

      Source |       SS       df       MS              Number of obs =     109

————-+——————————           F(  2,   106) =    2.13

       Model |  250.659437     2  125.329719           Prob > F      =  0.1236

    Residual |  6230.07909   106  58.7743311           R-squared     =  0.0387

————-+——————————           Adj R-squared =  0.0205

       Total |  6480.73853   108  60.0068383           Root MSE      =  7.6664

——————————————————————————

     rvidsch |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

————-+—————————————————————-

       abort |  -.8708947   .4901819    -1.78   0.078    -1.842728    .1009386

    deathpen |    .484386   .4736684     1.02   0.309    -.4547077     1.42348

       _cons |   4.801033   1.543066     3.11   0.002     1.741755    7.860312

——————————————————————————

What can we conclude from our results? Interpret the coefficients and discuss how much of the variance of videogame playing is accounted for by political factors.

b.) Undeterred, we press on, suggesting that perhaps political views are not the only answer. Below is a Model 2, multiple regression explaining school year videogame playing.

. regress rvidsch age height urban rvidsum rtvsch abort deathpen

      Source |       SS       df       MS              Number of obs =     107

————-+——————————           F(  7,    99) =   25.19

       Model |    4116.453     7  588.064715           Prob > F      =  0.0000

    Residual |  2311.36943    99  23.3471659           R-squared     =  0.6404

————-+——————————           Adj R-squared =  0.6150

       Total |  6427.82243   106  60.6398342           Root MSE      =  4.8319

——————————————————————————

     rvidsch |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

————-+—————————————————————-

         age |  -.5397808   .1949932    -2.77   0.007    -.9266896   -.1528719

      height |   .3511119   .1171413     3.00   0.003     .1186781    .5835456

       urban |   -.975658   1.214456    -0.80   0.424    -3.385401    1.434085

     rvidsum |   .4494623   .0414731    10.84   0.000     .3671706     .531754

      rtvsch |   .1787645   .0532984     3.35   0.001      .073009      .28452

       abort |  -.7029951   .3151186    -2.23   0.028    -1.328259   -.0777314

    deathpen |    .172909   .3069888     0.56   0.575    -.4362233    .7820413

       _cons |  -11.53183   9.254303    -1.25   0.216    -29.89437    6.830718

——————————————————————————

Discuss this model as compared to the last model. First, does it do a better job explaining videogame playing? How do we know? Write out the equation.

c.) Interpret the results of each variable on hours of video games played per week for Model 2. Be specific. Do the results surprise you? To aid in your discussion, below is a table depicting all of the variables used in the analysis:

    Variable |   Mean         Std. Dev.    Min        Max

————-+——————————————————–

     rvidsch |    5.191589    7.787158     0          35

         age |   21.7037      3.054824     18         43

      height |   68.89815     4.224295     56         80

       urban |    0.212963    0.4113103    0          1

     rvidsum |    6.925926   11.8416       0          60

————-+——————————————————–

      rtvsch |    9.634259   11.1978       0          100

       abort |    1.138889    1.506735     0 (choice) 4 (life)

    deathpen |    2.62037     1.545071     0 (con)    4 (pro)

d.)

In this final model (Model 3), we remove height from the equation.

. regress rvidsch age urban rvidsum rtvsch abort deathpen

      Source |       SS       df       MS              Number of obs =     107

————-+——————————           F(  6,   100) =   25.83

       Model |  3906.70149     6  651.116916           Prob > F      =  0.0000

    Residual |  2521.12094   100  25.2112094           R-squared     =  0.6078

————-+——————————           Adj R-squared =  0.5842

       Total |  6427.82243   106  60.6398342           Root MSE      =  5.0211

——————————————————————————

     rvidsch |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]

————-+—————————————————————-

         age |  -.5933422   .2017752    -2.94   0.004    -.9936586   -.1930259

       urban |   -.524767   1.252287    -0.42   0.676    -3.009269    1.959735

     rvidsum |   .4774664   .0419891    11.37   0.000     .3941612    .5607716

      rtvsch |    .167237   .0552408     3.03   0.003     .0576408    .2768332

       abort |  -.6352208   .3266126    -1.94   0.055    -1.283211    .0127692

    deathpen |   .2753666   .3170247     0.87   0.387    -.3536013    .9043346

       _cons |   13.30374   4.282819     3.11   0.002     4.806744    21.80073

——————————————————————————

Discuss what happened to views on abortion and its relationship to videogame playing between Models 1, 2, and 3. Why do you think this occurred? Use your knowledge of control variables to advance an explanation.

Note: Question 7 is designed to test your ability to explain these concepts clearly. Spend some time explaining and discussing. A few words likely will not do.

 

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