Skip to main content
Statistics LibreTexts

9.4: Which Analysis Should You Conduct?

  • Page ID
    5216
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    One of the most important concept that you need to understand is deciding which analysis you should conduct for a particular situation. To help you to figure out the analysis to conduct, there are a series of questions you should ask yourself.

    1. Does the problem deal with mean or proportion?
      Sometimes the problem states explicitly the words mean or proportion, but other times you have to figure it out based on the information you are given. If you counted number of individuals that responded in the affirmative to a question, then you are dealing with proportion. If you measured something, then you are dealing with mean.
    2. Does the problem have one or two samples?
      So look to see if one group was measured or if two groups were measured. If you have the data sets, then it is usually easy to figure out if there is one or two samples, then there is either one data set or two data sets. If you don’t have the data, then you need to decide if the problem describes collecting data from one group or from two groups.
    3. If you have two samples, then you need to determine if the samples are independent or dependent.
      If the individuals are different for both samples, then most likely the samples are independent. If you can’t tell, then determine if a data value from the first sample influences the data value in the second sample. In other words, can you pair data values together so you can find the difference, and that difference has meaning. If the answer is yes, then the samples are paired. Otherwise, the samples are independent.
    4. Does the situation involve a hypothesis test or a confidence interval?
      If the problem talks about "do the data show", "is there evidence of", "test to see", then you are doing a hypothesis test. If the problem talks about "find the value", "estimate the" or "find the interval", then you are doing a confidence interval.

    So if you have a situation that has two samples, independent samples, involving the mean, and is a hypothesis test, then you have a two-sample independent t-test. Now you look up the assumptions and the formula or technology process for doing this test. Every hypothesis test involves the same six steps, and you just have to use the correct assumptions and calculations. Every confidence interval has the same five steps, and again you just need to use the correct assumptions and calculations. So this is why it is so important to figure out what analysis you should conduct.

    Data Sources:

    AP exam scores. (2013, November 20). Retrieved from wiki.stat.ucla.edu/socr/index...08_APExamScore s

    Buy sushi grade fish online. (2013, November 20). Retrieved from http://www.catalinaop.com/

    Center for Disease Control and Prevention, Prevalence of Autism Spectrum Disorders - Autism and Developmental Disabilities Monitoring Network. (2008). Autism and developmental disabilities monitoring network-2012. Retrieved from website: www.cdc.gov/ncbddd/autism/doc...nityReport.pdf

    Cholesterol levels after heart attack. (2013, September 25). Retrieved from http://www.statsci.org/data/general/cholest.html

    Flanagan, R., Rooney, C., & Griffiths, C. (2005). Fatal poisoning in childhood, england & wales 1968-2000. Forensic Science International, 148:121-129, Retrieved from http://www.cdc.gov/nchs/data/ice/fat...ning_child.pdf

    Friday the 13th datafile. (2013, November 25). Retrieved from lib.stat.cmu.edu/DASL/Datafil...aythe13th.html

    Gettler, L. T., McDade, T. W., Feranil, A. B., & Kuzawa, C. W. (2011). Longitudinal evidence that fatherhood decreases testosterone in human males. The Proceedings of the National Academy of Sciences, PNAS 2011, doi: 10.1073/pnas.1105403108 Length of NZ rivers. (2013, September 25). Retrieved from http://www.statsci.org/data/oz/nzrivers.html

    Lim, L. L. United Nations, International Labour Office. (2002). Female labour-force participation. Retrieved from website: www.un.org/esa/population/pub...ty/RevisedLIMp aper.PDF

    Median income of males. (2013, October 9). Retrieved from http://www.prb.org/DataFinder/Topic/...s.aspx?ind=137

    Olson, K., & Hanson, J. (1997). Using reiki to manage pain: a preliminary report. Cancer Prev Control, 1(2), 108-13. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9765732

    Population reference bureau. (2013, October 8). Retrieved from http://www.prb.org/DataFinder/Topic/...gs.aspx?ind=25

    Seafood online. (2013, November 20). Retrieved from http://www.allfreshseafood.com/

    SOCR 012708 id data hotdogs. (2013, November 13). Retrieved from http://wiki.stat.ucla.edu/socr/index...D_Data_HotDogs

    SOCR data nips infantvitK shotdata. (2013, November 16). Retrieved from http://wiki.stat.ucla.edu/socr/index...tVitK_ShotData

    SOCR data Oct2009 id ni. (2013, November 16). Retrieved from http://wiki.stat.ucla.edu/socr/index..._Oct2009_ID_NI

    Statistics brain. (2013, November 30). Retrieved from http://www.statisticbrain.com/infidelity-statistics/

    Student t-distribution. (2013, November 25). Retrieved from lib.stat.cmu.edu/DASL/Stories/student.html


    This page titled 9.4: Which Analysis Should You Conduct? is shared under a CC BY-SA 4.0 license and was authored, remixed, and/or curated by Kathryn Kozak via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.