Hatco Customer Survey

2. Based on the scale of measurement for each variable listed below, which measure of central tendency is most appropriate for describing the data?

Efficient use of the statistical tool-regression will helps in deriving crucial relationship between variables that could offer significant pointers towards successful business decisions. Number crunching has emerged as the single most effective solution to pull up a declining businesses while on the other hand, the author advices customers to be vigilant in their business transactions that offer additional features at the same price. He also explains, how customer feedback extracted from market data and random surveys drives towards profitable decisions in the future for different sections of the society.

2. Based on the scale of measurement for each variable listed below, which measure of central tendency is most appropriate for describing the data?

* Correlation coefficient (R-squared) – This represents how well the independent variables (X) explain the response variable (Y).

2. Based on the scale of measurement for each variable listed below, which measure of central tendency is most appropriate for describing the data?

Analyze results - Graph the data from Table 4 and describe what your graph looks like (you do not have to submit a picture of the actual graph!).

A researcher found a significant relationship between a person's age, a, the number of hours a person works per week, b, and the number of accidents, y, the person has per year. The relationship can be represented by the multiple regression equation y = -3.2 + 0.012a + 0.23b. Predict the number of accidents per year (to the nearest whole number) for a person whose age is 42 and who works 46 hours per week.

There are various methods of collecting data such that the information collected can be used to draw inferences about the target population. The sales forecast is the key component for the problem statement and for accuracy it is important to know what consumers prefer over Best Buy. Participation in business surveys is usually voluntary and the quality of the results depends crucially on the willingness of enterprises to co-operate. A promising approach to getting high response rates is to make compliance as painless as possible

2. Identify all of the major dependent and independent variables and the level of measurement for each variable

the correlation is 0.668; the equation of regression is CREDITS=11.7475*AGE-174.356; the slope is 11.7475 which is positive; when the predictor variable AGE increase, the response variable CREDITS also strongly increase; for instance, when AGE increase by 1, the CREDITS will increase 11.7475. There are some outliers may affect the correlation. Based on the graphs and data above, we can find out a student who is older with a litter lower GPA, but has very higher credits; the student with higher credits also has high GPA.

In these tables we are looking at the relationship between the race and how much education one have completed. Observing at the chi-square, the P-value of .000, which lies beneath the cut off .05. Since the P-value is less than .05, there is a statistical significant relationship between the notion of race and education.

"There are several different kinds of relationships between variables. Before drawing a conclusion, you should first understand how one variable changes with the other. This means you need to establish how the variables are related - is the relationship linear or quadratic or inverse or logarithmic or something else" ("Relationship Between Variables ", n.d)

For this scatterplot the coefficient of determination is no longer very close to zero. This means that the slope may be significantly different from zero which in turn would mean that there is a significant correlation between the two variables. In order to check this we consider a hypothesis test for the slope of the regression line. The null and alternate hypotheses for this test are

So you first predict the independent variable, then look at the established relationships between that independent variable and the dependent ones to predict what the dependent variables will be. You then develop an equation that summarizes the effects of predictor variables.

Determine whether the correlation is significant Calculate and interpret the simple linear regression equation for a set of data Understand the assumptions behind regression analysis Determine whether a regression model is significant