Abstract
In this chapter, we continue our discussion of hypothesis testing methods. Here, we only consider hypotheses that are expressed in terms of a relationship between two variables. We start our discussion by focusing on situations where one variable is numerical and the other variable is binary. Typically, the numerical variable, called the response variable, is regarded as the primary variable of interest that captures a specific characteristic of the population that we are investigating. The binary variable, called factor, on the other hand, divides the population into two groups. Therefore, to evaluate the hypothesis regarding the relationship between the numerical variable of interest and the binary variable that defines the two groups, we investigate the difference between the two groups with respect to the characteristic represented by the numerical variable. Next, we discuss situations where both variables are binary. Finally, we talk about the situations where both variables are numerical.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kettunen, J.A., Harilainen, A., Sandelin, J., Schlenzka, D., Seitsalo, S., Hietaniemi, K., Malmivaara, A., Kujala, U.M.: Knee arthroscopy and exercise versus exercise only for chronic patellofemoral pain syndrome: a randomized controlled trial. BMC Med. 5, 38 (2007)
Levine, P.H.: An acute effect of cigarette smoking on platelet function: a possible link between smoking and arterial thrombosis. Circulation 48(3), 619–623 (1973)
Mackowiak, P.A., Wasserman, S.S., Levine, M.M.: A critical appraisal of 98.6°F, the upper limit of the normal body temperature, and other legacies of Carl Reinhold August Wunderlich. JAMA 268, 1578–1580 (1992)
Teasdale, N., Bard, C., Larue, J., Fleury, M.: On the cognitive penetrability of posture control. Exp. Aging Res. 19(1), 1–13 (1993)
Witte, A.V., Fobker, M., Gellner, R., Knecht, S., Floel, A.: Caloric restriction improves memory in elderly humans. Proc. Natl. Acad. Sci. USA 106(4), 1255–1260 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Shahbaba, B. (2012). Statistical Inference for the Relationship Between Two Variables. In: Biostatistics with R. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1302-8_8
Download citation
DOI: https://doi.org/10.1007/978-1-4614-1302-8_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-1301-1
Online ISBN: 978-1-4614-1302-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)