PSY 325 Assignment Calculate and Interpret Data 

PSY 325 Assignment Calculate and Interpret Data 

PSY 325 Assignment Calculate and Interpret Data 

Calculate and Interpret Data

            Developing more effective drugs is a crucial aspect of advancing medical treatments. Therefore, finding a more effective drug would require an effective trial process that would provide data that points out a safer n better drug.

Part 1

 Younger AdultsYounger AdultsOlder AdultsOlder Adults
PlaceboDrug APlaceboDrug A
Mean 26.4 10.4 26.2 23.4
Median 23 10 29 24
Mode 23 10  

            When interpreting the mean, mode, and median of two drugs being tested for effectiveness, these statistical measures can provide insights into the central tendencies of the data. The mean represents the average value of a set of data (Zhang et al., 2019). In the context of drug effectiveness, the mean can indicate the average response or outcome of participants who received a particular drug. By comparing the means of two drugs being tested, one can assess which one yields better results on average. In this case, Placebo works best on young adults, while drug A work best on older adults.

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            The mode represents the most frequently occurring value in a dataset. In drug effectiveness testing, the mode can indicate the treatment outcome most frequently among participants (Belan, 2020). Comparing the modes of two drugs can give one an idea of the most common response associated with each treatment. On the other hand, the median represents the middle value in a dataset when it is ordered from lowest to highest. It is helpful to assess the central tendency, especially if the data is skewed or has outliers (Fiolet et al., 2022). In the context of effectiveness between drug A and Placebo, the median can provide information about the midpoint of the response distribution.

PSY 325 Assignment Calculate and Interpret Data 
PSY 325 Assignment Calculate and Interpret Data 

Part 2

            The above bar graph, interpreting it involves understanding the data being represented, the variables involved, and the patterns or relationships that emerge from the graph. In this bar graph, the length of the bars will be effective in determining the drug’s effectiveness on a particular population (Möller, 2022). Each bar’s height or length represents the data’s magnitude or value for that particular category (Scalia et al., 2021). The greater the height or length, the higher the value associated with that category. In this case, Placebo is effective for both the young and adults. However, it is more effective on the young than adults. On the other hand, comparing the heights or lengths of the bars aids in identifying patterns or relationships within the data (Weissgerber et al., 2019). For instance, one would look for bars significantly different from others, indicating variations in the values across different categories. In this case, the action of drug A on both the young and adults has a significant difference. Drug A is not effective on young adults but comparatively effective on older adults. This relative comparison aids in considering relative differences between the bars. Besides, it aids in focusing on the proportions and ratios rather than absolute values.


Belan, S. (2020). Median and mode in the first passage under restart. Physical Review Research2(1), 013243.

Fiolet, T., Kherabi, Y., MacDonald, C. J., Ghosn, J., & Peiffer-Smadja, N. (2022). Comparing COVID-19 vaccines for their characteristics, efficacy, and effectiveness against SARS-CoV-2 and variants of concern: a narrative review. Clinical Microbiology and Infection28(2), 202-221.

Möller, H. J. (2022). Effectiveness studies: advantages and disadvantages. Dialogues in clinical neuroscience.  

Scalia, P., Schubbe, D. C., Lu, E. S., Durand, M. A., Frascara, J., Noel, G., … & Elwyn, G. (2021). Comparing the impact of an icon array versus a bar graph on preference and understanding of risk information: Results from an online, randomized study. Plos one16(7), e0253644.

Weissgerber, T. L., Winham, S. J., Heinzen, E. P., Milin-Lazovic, J. S., Garcia-Valencia, O., Bukumiric, Z., … & Milic, N. M. (2019). Reveal, don’t conceal: transforming data visualization to improve transparency. Circulation140(18), 1506-1518.

Zhang, R., Wu, T., Wang, R., Wang, D., & Liu, Q. (2019). Compare the efficacy of acupuncture with drugs in the treatment of Bell’s palsy: A systematic review and meta-analysis of RCTs. Medicine98(19).