research paper about heart disease and beverage consumption writing homework help

topic:heart disease and beverage consumption

sources can be used:

Directions: Individually, or in a group, select a topic of interest to you that has been researched using statistics with findings discussed in scholarly articles. You should have an introduction, background information, review of articles (at least 3), information on the statistical methods used by the articles, and a works cited page. You may include a table to compare the papers you review. The paper should be double spaced and while no length requirement exists, ~6 or 7 pages per person is reasonable.

For example, if you wanted to write about the wholesale electricity market you might provide some background information, such as:

The RTOs/ISOs operate a market for wholesale electricity where generators offer to sell electricity and load-serving entities bid to buy electricity (FERC, 2015). The RTOs/ISOs follow an economic dispatch where the least costly generating units are dispatched first; however, it is important to note that this dispatch is revised depending on system constraints (FERC, 2015). Locational marginal pricing (LMP) is used to incorporate transmission congestion in different areas of the market (FERC, 2015). LMP is composed of three components: the market-clearing price for energy, congestion, and energy losses (FERC, 2015). According to Olson, the organized markets for wholesale electricity should incentivize efficiency as inefficient generating units fail to clear the market and are unable to sell electricity while efficient plants reap higher returns (Olson, 1998).

You might cite and summarize the following paper:

Zarnikau, J., Woo, C. K., and R. Baldick. “Did the introduction of a nodal market structure impact wholesale electricity prices in the Texas (ERCOT) market?” Journal of Regulatory Economics 45 (2014): 194-208.

The authors use regression models to model the wholesale settlement price, or LMP, as a function of demand for electricity, amount of generation from nuclear plants, level of wind generation, and natural gas prices (Zarnikau et al, 2014). A dummy variable is used to signify the implementation of the zonal market with a value of 0 prior to December 1, 2010 and a value of 1 after that point in time (Zarnikau et al, 2014). The study shows that the introduction of the nodal market lowered prices between $0.54 and $1.42 per MWh in the three larger zones (Zarnikau et al, 2014). More specifically, the authors find that the introduction of the nodal market has resulted in average price declines in the North, Houston, and South zones of $0.91, $0.54, and $1.42 per MWh respectively (Zarnikau et al, 2014).

You might the go on to expand on regression models:

According to Sweeney et al, “multiple regression analysis is the study of how a dependent variable…

You may want to include a table, such as

Kury (2013)

Joskow (2006)

Fagan (2006)

Zarnikau, Woo, and Baldick (2014)

Research Questions

Has the establishment of ISOs/RTOs lowered the average electricity prices paid by customers of each state?

Have deregulatory initiatives lowered the price of residential and industrial electricity prices?

Do industrial customers face lower prices in states that are restructured?

Did the introduction of a nodal market structure impact

wholesale electricity prices in the Texas (ERCOT) market?

Unit of Analysis





Methods of Data Collection

Secondary data collection from EIA

Secondary data collection from EIA

Secondary data collection from EIA

Secondary data collection from ERCOT

Sampling Strategy

All 48 contiguous states were used

All U.S. states except for Idaho, which had data issues. Also, DC and Maryland were combined due to the way data was reported.

48 contiguous states except states that delayed or repealed restructuring (AR, CA, MT, OK, NM, and NV)

All zones within ERCOT

Analytical Strategy

Two-stage least squares regression analysis

Generalized least squares, state-specific fixed effects, and fixed effect plus a time trend

Counterfactual model and Two-stage least squares regression analysis

Regression analysis with a dummy variable

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