1. Compare and contrast descriptive vs. inferential statistics.
The first method used to describe a statistical measure is known as descriptive statistics. This kind of statistics describes the distribution of a set of data by means of specific measure of variables. It conveys the crucial properties of the population as they are without extrapolation. This kind of analysis makes it possible to understand the underlying concepts behind a population that would not be possible by studying individuals. Every variable in the study is taken into consideration .
On the other hand, inferential statistics is a method of defining a population by drawing conclusions on unknown aspects of a population from studying a sample of that same population. In this kind of statistical analysis, a sample of the population is put under study and the result is extrapolated to entire population (Portney, 2003). It is a useful method when looking to solve short-term problems.
2. Find and provide a short description of a study that utilized a descriptive statistic.
In understanding, with clarity, the phenomenon and reasoning behind a population, descriptive statistics is commonly used. A good example of such a study is the population census carried out periodically in the United States. One of the censuses was undertaken on April 15, 2000. A population census is the best example of a descriptive statistic since its variable is fixed but unknown.
A census is done to determine some key matters about the population such the population distribution in terms of race, gender, age and economic state of the people. This description is commonly referred to as ‘the Demography’ of the country. Demography is defined by some key variables, which are common to the entire population. These variables include amount of income per household, number of persons per household, number of households served by one medical centre, etc. In general, these variables are further are divided into two broad groups, that is, quantitative variable and qualitative variable.
Quantitative variable is one which can be measured infinitely or continuously. Such variable may include amount of income or number of people in a locality. On the other hand, qualitative variables refer to finite or discrete set of variables such as gender and religion.
In the end, the conclusion drawn in the 2000 census was done with actuality and without any assumptions or extrapolations. Central tendencies measures and skewness of distributions are some of the descriptive statistics aspects used.
3. Find and provide a short description of a study that utilized an inferential statistic
A good example of the use of Inferential Statistics was in the study performed by the New York Times on the popularity of the Iraq Invasion by the US Army in 2003. In the study, it was concluded that two-thirds of the Americans approved the incursion into Iraq. This assertion is however unusual since it not possible to ascertain that exactly two-thirds of the 300 million Americans approve this move (Portney, 2003).
The Times newspaper performed an Inferential Statistics on about 668 adults and inferred the conclusion to the nation. Claiming that the results of the few citizens reflect the true state of how the country feels towards such an act of war may be unacceptable. Therefore, to make such statistical meaning thorough sampling must be carried out to closely reflect a population.
Several statistical sampling theories have been suggested to help guide through the process of sampling to get the appropriate samples.
References
Portney, K. E. (2003). Taking sustainable cities seriously: economic development, the environment, and quality of life in American cities. Boston: MIT Press.
Portney, L. G., & Watkins, M. p. (2000). Foundations of clinical research: applications to practice. Upper Saddle River, NJ: Prentice Hall
