Research question

Psychology
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T-tests and Pearson R can be used to statistically analyze the industrial organization or the performance of a particular firm based on specific factors. One contentious area in the industrial sector is balancing the profit, price, quantity and time. This paper assesses how the t-test for dependent samples, t-test for independent samples and Pearson r can be used to answer correlations between these variables. The question posed is, what is the degree of correlation between profit and quantity?
T-tests are statistical analysis used to assess if two means significantly differ from each other. Dependent and independent samples t-tests compare the means of two different groups of the same variable on the same measure (Leatham, 2012). In this case, the average for the profit margin over a set period of time is calculated. This could be the paired samples of the profit margins with the quantity of input. The dependent sample assesses if the mean difference between the paired variables is any significantly different from zero. A question that can be answered by the T-tests is the correlation between the profit margins for a machine operated at an accelerated output of one item per second and one item per second over a day?
On the other hand, the independent t-test assesses if there are significant differences between the means for two unrelated groups, i.e. when the input quantity is assessed for profit against the time as an independent variable.

Each t-test has a significant value next to it showing its level of significance. If the significance value is less than 0.05, the results are significant else they are not significant. A significant figure means that the difference between the mean can be treated as real and not accidental.
Pearson’s r assess if there is a significant linear association between two scores. It tests whether the values of one element increase as the other variable also increase (or decrease). The value of ‘r’ takes a value between -1 and +1 (“Data Analysis – Pearson’s Correlation Coefficient,” 2018). Positive r values show a direct proportionality between the scores on the two variables. On the other hand, negative r values show an inverse proportionality between the scores. A zero r value shows that there is no linear correlation between the two scores. It means that scores of the first independent variable reveal no substantial information about the scores of the second variable. A positive r-value in the graph of profit against quantity would indicate that the relationship is directly proportional.

References
Leatham, K. (2012). Problems Identifying Independent and Dependent Variables. School Science And Mathematics, 112(6), 349-358. http://dx.doi.org/10.1111/j.1949-8594.2012.00155.x
Data Analysis – Pearson’s Correlation Coefficient. (2018). Learntech.uwe.ac.uk. Retrieved 10 March 2018, from http://learntech.uwe.ac.uk/da/Default.aspx?pageid=1442