Instructions

Written projects:

Must be typed, double-spaced, in 12-point Times New Roman or Arial font, with one-inch margins

Must have the title page in APA-7th edition style

Must have in-text citations in APA-7th edition style

Must have reference list in APA-7th edition style; note that you must reference the data you are using for the project

Must be prepared using word processing software (Microsoft Word preferred)

Data Exercise 2

The purposes of the data exercises are to:

• enhance your skills at finding current economic data on the web;
• improve your skills at data presentation and explanation;
• provide you the opportunity to learn how to analyze economic data and, very importantly, to explain what it means in short, turning data into useful information; and
• how to present that information to a reader in a clear and understandable form.

For Data 2:

Your objective is to compare two related economic variables and see if you can identify a relationship between them. You should first look at the variables separately, then in relationship to each other.

1. You will select two related economic variables that you have studied during the relevant weeks.
2. Find appropriate data on both variables.
3. Present that data in a clear graphic or tabular form (or both if appropriate).
4. Explain what the data showsdiscuss/explain the data.
5. Explain what the data meansgive meaning to what the data shows.
6. Explain why it matterswhat is the economic importance or usefulness of what you found in your data analysis and discussion.

Points 4 and 5 initially seem to be about the same thing and they are close in meaning. Point 4 is the process of walking the reader through the data presented in the table or graphic. Point 5 is explaining to the reader what that data means. In other words, tell the reader what the data is and explain what it means. Remember this is a process of giving meaning to data. Standing alone, data is just numbers. Your task is to give those numbers a context and a meaning that converts numbers into information.

Points to Remember:

• Stay calm, this is actually a fun assignment and a great learning experience, and it is not as daunting as it first appears.
• You have to have real world data; i.e., numbers.
• You have to have citations in the body of your report.
• Tables and graphics need a citation immediately following the table or graphic; if you create the table or graphic, then the citation is to the source of the data.
• You need references at the end of the report.

Format Requirements:

• upload your report in MS Word format (.doc or .docx); if you use another format, ask before uploading to be sure I can open it;
• double space the paper;
• have a title page;
• have a reference page;
• excluding the title and reference pages, the report should be 3 to 5 pages; and
• if you use an appendix, that would be in addition to the 3 to 5 pages.

You have lots of choice as to your variables for the data exercises. If you want to email me your choices for some initial feedback before you get too far into the process, that will be fine. I’ll be happy to provide specific suggestions and guidance in response to your initial efforts, but I do not make the variable choices for you; that is part of the learning experience.

Sources to use:

https://www.bea.gov/data/gdp/gross-domestic-product

compare two related economic variables and see if you can identify a relationship between them.

Introduction

If you are a data analyst, it’s easy to come up with two variables that seem to be related. There may be a relationship between the price of gas and the temperature in your city; however, it doesn’t mean that one causes the other. In this lesson we will explore how to identify if there is a relationship between two economic variables.

Does one variable change as the other changes?

To test a relationship, you will need to measure two related economic variables. If they are related in some way, then you should be able to see changes in one variable when the other changes. For example:

• If an economy is growing and unemployment goes down because of this growth, then we would expect that wages would also go up. However, if workers are still unemployed but earning more money per hour worked (due to greater demand for their services), then we might not see this increase in wages as much as expected.

Does one variable cause the other to change?

In the world of economics, there’s a tendency to think that correlation equals causation. Correlation means that two variables are related in some way; for example, if you look at your bank account balance and then check the weather forecast for tomorrow (or any other day), you’ll probably find that they’re pretty closely associated. When this happens, people tend to assume that one causes the other—that is, when we see an increase in one variable (such as checking our bank balances), we think something must be happening with respect to another variable (like our jobs). But this isn’t always true!

In fact, it can sometimes be difficult even for experts like myself and my partner David Rolfe who have studied these things extensively over many years not only because data collection methods change over time but also because statistical analysis has yet to fully develop within most fields of study including economics itself.*

Are there any patterns that you can find?

• Are the two variables moving in the same direction?
• Are they moving in opposite directions?
• Are they moving at the same rate, but in opposite directions?
• Are they moving at different rates, but also in the same direction.

A relationship between two variables does not always mean that one causes the other.

The relationship between two variables does not always mean that one causes the other. For example, if you have a variable that is increasing and another variable that is decreasing, then it might be tempting to say that as long as your increase in variable X continues, your decrease in variable Y will also continue. But this doesn’t necessarily hold true because some other factors could cause either or both of these changes: for example, if there’s an economic recession (which increases unemployment), then it may take longer for people’s incomes to recover; thus by extension their spending power won’t increase at the same time as their income does—leading them not only feel less confident about their future but also make fewer purchases today than they would have otherwise because they’re worried about whether tomorrow will be better or worse than today!

Conclusion

The relationship between two variables is a very important part of economics. But there are many cases where you will see a relationship but don’t know which one caused the other or if they are independent.

Having your own intuition about the direction of causality is crucial because if you are wrong then it could cost you money. For example, if you think that high inflation causes low interest rates then when interest rates increase your company may be less able to pay its debts and bankruptcy may be inevitable!