Inferential - Statistics Project Example

The data sets are divided into two sets; Android, Windows and Others representing the operating systems in the market and a dependent variable Smartphone on the category indicating the total cell phone sold with the operating system. The independent variables are the App is representing the App store, GUI represents the Graphical User Interface of the smartphone and the Functionality representing the functions carried out by the operating systems and the apps. The data is bivariate data as two variables are measured in a single study (William Mendenhall III, 2013).

We calculated the operating system market share and the customer buying behavior towards the software capabilities of the smartphone. Most consumers prefer smartphones running on Android platform; on average 10 Android phones are sold daily. The consumer‘s are influenced by the app store on the phone, with 9 people every day says that the app store matters to them most. The positive coefficient indicates the directional effects of the independent variables and the effect they will have on the depend variable smartphone.

Thus, with an increase in App, GUI or Functionality results to increase in sales of smartphones. Meaning that the consumer behavior depends on the software installed or can be installed on the gizmo. Goodness to fit ≥ 0.80 or 80% and we reject Reject H0 if p-value ≤ α, where α is the level of significance for the test (David R. Anderson, 2011). Thus p-value ≥ 0.0000, thus the null hypothesis is accepted. At 95% confidence level (1.869, 5.088), this are plausible values of parameter where mean may lie; thus, we expect more consumers to be influenced by App store parameter in smartphone.

Thus we expect the sales of Android phones to increase with the same parameter as they are the market