Abstract Case Solution
Intervening, Extraneous, and Moderating Variables
An intervening variable is described as a hypothetical variable that is typically used to explain the link between other variables, such as independent and dependent variables. Extraneous variables are described as variables that are not purposefully being studied. These variables are typically not a main focus in the study, but end up having an effect on the dependent variable. Moderating variables can change the effect between the variables, those being the independent and dependent variable. This variable can positively or negatively influence the connection between the independent and dependent variables. These variables help to explain the connection between the two. Through the study, it is apparent that to draw a valid conclusion these variables would have to be controlled in the most efficient way. Using nine very diverse countries allowed them to mitigate the risk of becoming too centralized in one specific business culture that these nations tend to have. Through expanding the range, they could control variables such as age, gender, education level, and social aspects. These all in a way can affect the outcome of the experiment, but are not the dependent nor the independent variable.
Variable Control in a Causal Study
A causal study attempts to ascertain whether a variable affects or changes another variable (Jeffreys 2018). A causal study is an experimental study; therefore, controlling the variables is important to the experiment. For this study, government agencies created and offered programs designed to increase entrepreneurship and increased access to educational services. To accommodate for the lack of control of extraneous variables, data was used from nine nations. The research design sought to determine whether access to programs, education, and promotion affected entrepreneurship growth in countries involved in the study. In other words, researchers measured whether positive interest in entrepreneurship increased with more promotion, programs, and education offered by government agencies.
A causal study controls the variables to measure the effect on other variables. Unlike a descriptive study, a causal study experiments with variables in an attempt to discover how manipulation of variables changes other variables. A descriptive study performs a cross-sectional or longitudinal study and does not generally manipulate the variables (Jeffreys 2018). A causal study, however, manipulates the variables to ascertain the degree of impact on other variables. This study was conducted in a field environment; in other words, this study was performed outside of a lab setting without total control of factors potentially influencing the variables.
The study measured how entrepreneurship increased based on access to programs and education. For example, researchers measured how programs directed toward potential women entrepreneurs increased interest in becoming an entrepreneur. Programs were also offered to different age groups than the norm to discover the correlation between these programs and higher interest in entrepreneurship. However, longitudinal studies were developed for other countries lacking in variable control. These longitudinal studies attempted to measure the effect on economic growth with a new conceptual model involving cultural, economic, physical, and political factors (Schindler 2019).
Impact on Study
In chapter 5, Schindler states, “probability sampling is based on the concept of random selection - a controlled procedure that assures that each case is given a known nonzero chance of selection” (Schindler, 2019, p. 96). The researchers’ research design was simple random sampling. The researchers gathered information from two rounds of adult population surveys in different countries. The two rounds of adult population surveys were 1,000 randomly selected adults from the study’s participating countries. The researchers completed surveys by phone, face-to-face interviews, and an interview with 4-39 national experts (key informants) in each county to collect data to measure entrepreneurial activity and attitude.............................
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