Ordinarily,weather reports offer information concerning high, low, and averagetemperatures on any given day. The average figure is thus determinedmostly by examining the high and low-temperature records.Nonetheless, the approach ignores other variables that are essentialin identifying the real average for a given day. It is possible toget a more reliable figure by using the descriptive analysisapproach hence, instrumental in making important decisions such astraveling. In descriptive statistics, one is required to tallyresponses, as well as, compute percentages for different timings. Assuch, assumptions and estimations are eliminated when identifying thecorrect figures (Sansuddin et al., 2011).
Itis hard to determine the average temperatures from records compiledover an extended period due to the random changes in the weatherconditions. It is also expected that techniques for both analyzingand recording temperatures have changed over the said time. Further,the variations in the physical environment are likely to presentchallenges in generating credible and dependable temperatureaverages. As such, getting the right measurement will require one toidentify other variables and statistical tools that can help inachieving better results (Leblois, Quirion, Alhassane, & Traoré,2012).
Theinternal level of measurement is appropriate for consideration as itdoes not only classify measurements but also identifies the distancebetween each interval on a scale. In the case above, the approachconsiders other variables such as time of the day and units ofmeasure. Measuring temperatures in centigrade is a good approachsince it uses the internal level of measurement. The distance between230Cand 250C is the same as the distance between 110 C and 130C. The averagescan later be placed into groups that are based on the timings of theday. Determining the frequency distribution helps to come up with achart that is essential for making a decision when traveling(Freemer, 2011).
Freemer,G. (2011). Measuring temperature by indirect means.Chemical Engineering Progress, 107(11),24-27.
Leblois,A., Quirion, P., Alhassane, A., & Traoré, S. (2014). index drought insurance: An ex ante evaluation for millet growers inNiger.Environmental and Resource Economics, 57(4),527-551.
Sansuddin,N., Ramli, N. A., Yahaya, A. S., Yusof, N. F., Fitri, Md, . . . Al.
Sansuddin,N, Ramli, N.A., Yahaya, A.S., Yusof, N.F., Ghazali, N.A., &Madhoun, W.A. (2011). Statistical analysis of PM10concentrations at different locations in Malaysia.