1. Describe two (2) research scenarios where cluster analysis may be used as the data analysis strategy.
When a business wants to introduce a new product, it must first determine its target market. The corporation can discover unique groups of customers that may react differently to the new product by performing a cluster analysis on its customer data (taking factors like age, income, historical purchasing behavior, geographic location, etc. into consideration). For instance, a segment might include high-earning young adults who were early adopters of technology, and they could be targeted with certain marketing techniques.
Cluster analysis can be used by educational institutions to classify students according to factors including performance, learning preferences, and interests. This can aid in developing effective academic programs, personalizing teaching strategies, and identifying students who may require further support.
2. Describe two (2) research scenarios where one way manova may be used as the data analysis strategy.
The two dependent variables are “short-term memory recall” and “long-term memory recall,” while the independent variable is “lecture duration,” which has four independent groups: “30 minutes,” “60 minutes,” “90 minutes,” and “120 minutes.” You could use a one-way MANOVA to determine whether there were differences in students’ short-term and long-term recall of facts based on three different lecture lengths.
They randomly assigned 33 participants to one of three groups by a researcher. The first group interacts with an online service to obtain technical dietary information. Group 3 receives the same information from a video clip produced by the same nurse practitioner, while Group 2 receives the same information from a nurse practitioner. To see if there is a difference between the presentation types, the researcher examines three ratings of the presentation: difficulty, usefulness, and importance. The interactive website is the most economical way to offer the information, thus the researcher is particularly interested in if it is superior.
3. Describe two (2) research scenarios where linear discriminant analysis may be used as the data analysis strategy.
LDA is extremely useful in the medical profession for categorizing patient diseases based on a variety of factors relating to the patient’s health and the current medical treatments. It categorizes disease as mild, moderate, or severe based on these criteria. The doctors can alter the treatment’s pace by using this classification to their advantage.
LDA is currently being used in customer identification. It means that with the aid of LDA, we can quickly recognize and choose the elements that can designate the demographic of people who are most likely to buy a particular product in a mall. When trying to pinpoint a specific demographic of shoppers who frequent a particular mall, this can be useful.
4. Describe two (2) research scenarios where factor analysis may be used as the data analysis strategy.
To find “factors” that can explain a range of test outcomes, factor analysis is performed. For instance, intelligence studies have shown that persons who perform well on verbal aptitude exams also perform well on other verbal aptitude tests. Researchers used factor analysis to identify one factor, commonly referred to as verbal intelligence, which reflects an individual’s capacity to solve challenges involving verbal skills.
In disciplines including finance, biology, psychology, marketing, operational research, etc., factor analysis is applied. People may react similarly to enquiries regarding a product’s utility, cost, and durability when asked about consumer satisfaction, for instance.
5. Mr. Smith wants to determine the dimensions, if any, along which certain attitudinal variables may be related to certain health characteristics. The attitudinal variables are attitude toward the role of women (attrole), toward locus of control (control), toward current marital status (attmar), and toward self (esteem). Larger number indicate increasingly conservative attitudes about the proper role of women, increasing feelings of powerlessness to control one’ fate (external as opposed to internal locus of control), increasing dissatisfaction with current marital status, and increasingly poor self-esteem). The health variables are mental health (menheal), physical health (phyheal), number of visits to health professionals (timedrs), attitude toward the use of medication (attdrug), and frequency-duration measure of the use of psychotropic drugs (druguse). Large numbers reflect poorer mental and physical health, more visits to doctors, greater willingness to use drugs, and more use of them. Use the data ‘canondat.sav’ for this problem. Screen the data for normality and multivariate outliers. Perform necessary transformation of the variables, if necessary. Conduct a canonical correlation analysis and determine what dimension(s) of attitude and health variables may be related. Report your results in 2-3 paragraphs, including summary tables.