Whether Men Spend on Moms More than Women – Statistics Project Example

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The paper "Whether Men Spend on Moms More than Women" is an excellent example of an essay on sociology. This essay uses the articles titled; Mothers Day: Men spend more on mom than women: survey published on Canada. com as a basis for the discussion on the population mean, confidence interval and margin of error. This article was authored by Misty Harris of Postmedia News and is dated 2012, May 7. It contains the findings of two surveys conducted by the Bank of Montreal (BMO) of Canada and the National Retail Federation (NRF) of the United States of America.

For the purposes of this paper, the NRFs survey will be used because the margin of error has been included. NRF interviewed 8700 adults to find out the amount of money they expected to spend during the mother’ s day. From the analyzed data, it was established that men had budgeted an average of $ 189.74 compared to women $ 117.42. The purpose of carrying out any form of survey is to use the results of analyzed data to make general conclusions about a bigger population.

The population comprises all objects under study, for instance, American voters, and employees of an organization and users of social networking sites. A population might be very large making data collection from all the individuals in a population impractical. Using the NRF case, it will be very difficult to interview approximately 203 million adult Americans. To solve this problem statisticians use a representative population referred to as the sample in surveys. Similarly, NRF uses 8700 adults to represent the adult population. The sample was chosen through a simple random sampling technique.

This method ensures that each individual has an equal chance of representing the population hence biasness is minimized (Dattalo, 2009). Once the data from the sample has been analyzed, inference about the population is made from the sample. Surveys involve the measurement of quantities called parameters. Parameters are numerical that tells us more about a population (Moore, 2009). For this survey, the parameter underdetermination was the average spending of adult Americans on mother’ s day. The study established that men spend slightly more than women on their moms.

The average spending was computed by summing up all men's and women's budgets and then dividing each by sample size. In the end, this is taken as the population means and from it, we get conclusions such as men are more attached to their mothers than women. In as much as the sample mean may be taken as the population average, there are chances that the two differ. In other words, adult men might be spending more or less than dollars $ 189.74. These deviations are recognized by including the margin of error whenever the sample mean is being quoted.

In the case of the NRF survey, a 1% margin of error is given. This translates to ± 1.90$ and ± 1.17$ allowance for men and women average spending respectively. The confidence interval or the range of values that carries the population average spending lies between 187.84 to 191.64 and 116.30 to 118.59 for men and women respectively. Hence, the margin of error is half the confidence interval. The margin of error expresses how close the sample data represent the population characteristics (Rumsey, 2011).

Therefore, a larger margin of error means less confidence in the results. To minimize the margin of error, statisticians use the larger sample as the margin of error is inversely proportional to the square root of the sample size. A 1% margin of error reported in the NRF survey is acceptable in most surveys. As a result, the NRF survey may be deemed to be reliable.


Dattalo, P. (2009). Strategies to approximate random sampling and assignment. Oxford: Oxford University Press.

Misty, H. (2012, May 7). Mothers Day: Men spend more on mom than women. Retreived fom http://www.canada.com/life/Mother+spend+more+than+women+survey/6579168/story.html

Moore, D. (2009). The basic practice of statistics. New York: Palgrave Macmilllan.

Rumsey, D. (2011). Statistics for Dummies. John Wiley & Sons.

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