Dataset #2 – Star War Film Data

Description: Weekly domestic box office revenues for the 8 Star War films

Research ‘Question’: Find a ‘best’ linear model to predict Star War revenue/day using the number of theaters, number of weeks since release, film number, and release year.

“There is no luck. Only good marketing” Please provide your opinion about this statement. Please use examples and academic sources to support your discussion. - Discussion in 300 words - Use at least 2 examples to illustrate your discussion - Use at least2 academic sources to support your argument.

In May 2004, a Gallup Poll of adults’ attitudes toward Health Maintenance Organization (HMOs) found that 41% of adults had little or no confidence in HMOs, 38% had some confidence, 17% had a great deal or quite a lot of confidence, and 4% had no opinion (USA TODAY, June 22, 2004). Let us denote these outcomes as L, S, G, and N, respectively. A recent random sample of 500 adults yielded the frequency distribution given in the following table.   Response L S G N Frequency 212 198 82 8

a. Determine the rejection region.

b. Using the 2.5% significance level, can you conclude that the current distribution of opinions differs from the distribution of May 2004?

1. It has been suggested that global warming may increase the frequency of hurricanes. The table given below shows the number of major Atlantic hurricanes recorded annually before and after 1990.

Does this data is sufficient enough to claim that the number of annual hurricanes increased since 1995? Do the test at 8% significance level. To do the test, answer the following: a. Write down the null and alternative hypotheses. b. Get the excel output and answer the following: i. Fill the cell with the p-value of the test with green color ii. Fill the cell with the test statistic of the test with yellow color

We had two financial crises since 2000, 2000 dot.com bubble, 2008-2009 financial crisis. From FRED website, find the following data from 1995 to 2013, and make a graph. Explain the general trends of each series, and compare them between the two crises.

1. Money supply (M2)
2. Nominal GDP
3. Velocity of Money
4. Consumer Price Index

An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead).  Consumers, of all income and wealth classes, were surveyed.  Every year, 1500 consumers were interviewed.  The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually.  Below is the data shown for the last 24 years.

Date                 X                     Y (in thousands of dollars)

1994                79.1                 55.6

1995                79                    54.8

1996                80.2                 55.4

1997                80.5                 55.9

1998                81.2                 56.4

1999                80.8                 57.3

2000                81.2                 57

2001                80.7                 57.5

2002                80.3                 56.9

2003                79.4                 55.8

2004                78.6                 56.1

2005                78.3                 55.7

2006                78.3                 55.7

2007                77.8                 55

2008                77.7                 54.4

2009                77.6                 54

2010                77.6                 56

2011                78.5                 56.7

2012                78.3                 56.3

2013                78.5                 57.2

2014                78.9                 57.8

2015                79.8                 58.7

2016                80.4                 59.3

2017                80.7                 59.9

Question:

1. Construct the linear regression model for the dollar amount spent on luxury goods and services.

The data below is the total spending (in millions of dollars) on drugs and other non-durable products for your assigned state (or DC). You need to convert this data to spending per capita in constant 2019 dollars.

Go to the FRED database at https://fred.stlouisfed.org/

Search for the PCEPI. Change the frequency to annual. Using that price index (this is a national index; there isn't a PCE index for each state), convert the following to 2019Q3 dollars.

Again using the FRED database, find the population for your state. The symbol is usually the two letter abbreviation for the state and POP. New York, for example, would be NYPOP.

Using this information, covert the spending below into spending per capita, in 2019Q3 dollars. Keep in mind that the values below are in millions of dollars and you want your answers in dollars.

Enter your results for every even-numbered year in the answer

Alaska

The general fund budget (in billions of dollars) for a U.S. state for 1988 (period 1) to 2011 (period 24) follows.

(a)

Construct a time series plot.

What type of pattern exists in the data?

The time series plot shows a horizontal pattern.

The time series plot shows a nonlinear trend.    

The time series plot shows a seasonal pattern.

The time series plot shows a linear trend.

(b)

Develop a linear trend equation for this time series to forecast the budget (in billions of dollars). (Round your numerical values to three decimal places.)

T_t =

(c)

What is the forecast (in billions of dollars) for period 25? (Round your answer to two decimal places.)

$ _______ billion

Despite the growth in digital entertainment, the nation’s 400 amusement parks have managed to hold on to visitors. A manager collects data on the number of visitors (in millions) to amusement parks in the United States. A portion of the data is shown in the accompanying table.

B-1) Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.)

B-2 Calculate the MSE for both trends. (Do not round estimates or intermediate calculations. Round final answers to 2 decimal places.)

b-3. By comparing MSE, which of the above methods perform better? Exponential or Linear?

c-1. Using the model of best fit, make a forecast for visitors to amusement parks in 2008. (Do not round estimates or intermediate calculations. Round your answer to 1 decimal place.)

c-2. Using the model of best fit, make a forecast for visitors to amusement parks in 2009. (Do not round estimates or intermediate calculations. Round your answer to 1 decimal place.)