Test of Correlations

Saiyidi Mat Roni () and Hadrian Geri Djajadikerta ()
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Saiyidi Mat Roni: Edith Cowan University, School of Business and Law
Hadrian Geri Djajadikerta: Edith Cowan University, School of Business and Law

Chapter Chapter 8 in Data Analysis with SPSS for Survey-based Research, 2021, pp 143-160 from Springer

Abstract: Abstract During the COVID-19 pandemic where many cities were in a strict lockdown, hence people drove less. Demand for the fuel was so low that in April 2020 the crude oil was at USD8.62 per barrel compared to USD61.22 before the freefall in December 2019. Taking advantage of the cheap fuel, a lucky few who were allowed to drive experimented with different types of fuel, from the standard unleaded RON 91 which was cheap, to an expensive but was more affordable premium RON 98 to see which one gives more miles per litre. We can find a correlation between the fuel type and the distance travelled using Pearson’s correlation test. If the result is statistically significant, we can confidently say that statistically speaking, there is a correlation, perhaps more expensive fuel gives more mileage. Hence, we use RON 98 regularly (until the price goes up again). In this chapter, we explain the correlation test between two variables that you can use for your survey data. For example, you want to investigate if attitude toward a brand is related to intention to purchase the product. We also teach you a bootstrap correlation test which provides a more stable result in most cases. This chapter, as the name speaks, is about correlation; and correlation is not a causation. The more expensive fuel correlates with the distance driven but the variable causing the extra miles to be possible is the octane level in the petrol (not the price we pay for). For this, you need the regression analysis to further investigate the causation. We discuss the regression in Chap. 9 .

Keywords: BCa; Bias corrected accelerated; Bootstrap; Confidence interval; Correlation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/978-981-16-0193-4_8

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