Needs To Be Done In Excel 16 Table 1 2 Gives Data On The Con

Needs To Be Done In Excel16table 1 2 Gives Data On the Consumer Pric

Needs to be done in Excel 1.6. Table 1-2 gives data on the Consumer Price Index (CPI), S&P 500 stock index, and three-month Treasury bill rate for the United States for the years. Plot these data with time on the horizontal axis and the three variables on the vertical axis. If you prefer, you may use a separate figure for each variable. What relationships do you expect to find between the CPI and the S&P index and between the CPI and the three-month Treasury bill rate? Why? For each variable, “eyeball” a regression line for the scattergram. 1.7. Table 1-3 gives you data on the exchange rate between the U.K. pound and the U.S. dollar (number of U.K. pounds per U.S. dollar) as well as the consumer price indexes in the two countries for the period. Plot the exchange rate (ER) and the two consumer price indexes against time, measured in years. Divide the U.S. CPI by the U.K. CPI and call it the relative price ration (RPR). Plot ER against RPR. Visually sketch a regression line through the scatterpoints. 1.8. Table McGraw-Hill Higher Education, contains data 1247 cars from 2008. Is there a strong relationship between a car’s MPG (miles per gallon) and the number of cylinders it has? Create a scatterplot of the combined MPG for the vehicles based on the number of cylinders. Sketch a straight line that seems to fit the data. What type of relationship is indicated by the plot?

Paper For Above instruction

Analysis of Economic Indicators and Vehicle Data Using Excel

Understanding the relationships between economic indicators such as the Consumer Price Index (CPI), stock markets, and interest rates is vital for economic analysis and forecasting. Similarly, examining vehicle data like fuel efficiency in relation to the number of cylinders provides insights into automotive engineering and consumer preferences. This paper discusses how to analyze such data using Excel, focusing on plotting variables, estimating relationships through regression, and interpreting these relationships.

Plotting Economic Data: CPI, Stock Index, and Treasury Rates

The first task involves analyzing data related to the U.S. Consumer Price Index (CPI), the S&P 500 stock index, and three-month Treasury bill rates over specific years. The primary goal is to visualize these variables over time. Using Excel, one can create line charts or scatter plots with time on the horizontal axis and each variable on the vertical axis. Creating separate figures for each variable enhances clarity and allows for comparison.

When visualizing the CPI against the S&P 500, a positive correlation might be hypothesized since rising inflation could coincide with economic growth reflected in the stock market. Conversely, the relationship between CPI and the Treasury bill rate is often expected to be inverse; as inflation increases, interest rates tend to rise to compensate lenders for inflation risk. Eyeballing scatterplots and fitting regression lines helps identify linear trends and possible correlations.

Analyzing Exchange Rates and Relative Price Rations

The next dataset involves the exchange rate between the U.K. pound and U.S. dollar, along with the consumer price indexes in the UK and USA. Plotting the exchange rate and CPI data over time reveals trends, fluctuations, and possible causal relationships. The division of U.S. CPI by U.K. CPI yields a relative price ratio (RPR), indicating the relative inflation levels between the two countries.

Plotting the ER against the RPR visually illustrates the relationship between relative prices and exchange rates. A regression line can be sketched to interpret whether ER moves proportionally with changes in RPR, revealing insights about purchasing power parity (PPP) and exchange rate dynamics.

Vehicle Fuel Efficiency and Cylinders

The final dataset from McGraw-Hill Higher Education relates to 1247 cars from 2008, focusing on miles per gallon (MPG) and the number of cylinders. Constructing a scatterplot of MPG versus cylinders helps identify the nature of their relationship. Typically, vehicles with fewer cylinders tend to have higher MPG, indicating an inverse relationship.

Drawing a straight line through the scatterplot's points—by eyeballing—helps gauge the trend. The observed pattern generally suggests a negative linear association, which can be quantified through regression analysis. Understanding this relationship is essential for automotive design and consumer decision-making regarding fuel efficiency.

Conclusion

Excel provides various tools for visualizing and analyzing data to uncover relationships among economic and automotive variables. Plotting time series data, creating scatterplots, and estimating regression lines facilitate intuitive understanding of the data. These insights support economic forecasting, policy-making, and engineering decisions, emphasizing the importance of effective data visualization and interpretation.

References

• Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and Applications. Cambridge University Press.
• Wikipedia contributors. (2023). Consumer Price Index. Wikipedia. https://en.wikipedia.org/wiki/Consumer_price_index
• Federal Reserve Economic Data (FRED). (2023). Consumer Price Index and Interest Rates. Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org
• Investopedia. (2023). Understanding Exchange Rates. https://www.investopedia.com/terms/e/exchangerate.asp
• U.S. Bureau of Economic Analysis. (2023). International Data: U.S. CPI. https://www.bea.gov
• UK Office for National Statistics. (2023). Consumer Price Inflation. https://www.ons.gov.uk
• U.S. Department of Energy. (2023). Fuel Economy Data. https://www.fueleconomy.gov
• Automotive Data. (2008). Car Model Specifications Dataset. McGraw-Hill Higher Education.
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• Klein, L., & Ross, D. (2017). Fundamentals of Data Analysis for Economics and Business. Springer.