Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Descriptive Statistics:
Carrying out an extensive analysis the data was not a subject to ambiguity and there were no missing values. Below are descriptive statistics that have been constructed after identifying no ambiguous or missing data for each variable that were included:
The 'N' in the descriptive statistics shows the total number of data items that is present which is 1519, however 'N*' reveals the number of items that are missing data which is 0.
The mean portrays central tendencies with the inclusion of all the data provided but the trimmed mean displays central tendency of data with 5 to 25 percent being discarded as it may include extreme data sets which can be relevant as it is less sensitive to outliers. Observing the mean and trimmed mean from the descriptive statistics for wfood, income, totexp and nk and age suggests they have a small change between their mean and trimmed mean which isn't highly significant.
The standard deviation measures the spread of data as well as the variance however the variance is the square root of standard deviation. Wfood and nk have low standard deviation and variance values; age has relatively high standard deviation and variance values where as on the other hand totexp and income has a high standard deviation and variance value. As there is a huge data sample many extreme data sets are established.
The coefficient of variation is the ratio of standard deviation to the mean which is a measure of dispersion of data of a variable. Wfood, totexp, income, age and nk have relatively high coefficient of variance which indicate that data is relatively highly dispersed from income being the most dispersed to age being the least dispersed.
Theories of Business forecasting
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
Why are graphs and tables useful when examining data? A researcher is comparing two middle school 7th grade classes. One class at one school has participated in an arts program
The management at Superior Health Care System Incorporated recently purchased several new facilities including the central patient information management center. This purchase will
The 4 assumptions of regression: 1. Variables are normally distributed 2. Linear relationship between the independent and dependent variables 3. Homosced
In New Jersey, banks have been charged with withdrawing from counties having a high percentage of minorities. To substantiate this charge, data is presented in the table below conc
Coefficient of Determination The coefficient of determination is given by r 2 i.e., the square of the correlation coefficient. It explains to what extent the variation
What type of correlation coefficient would you use to examine the relationship between the following variables? Explain why you have selected the correlation coefficients. A. Re
Complete the multiple regression model using Y and your combined X variables. State the equation. Next, make sure that you evaluate overall model performance with the Anova table
Your company has developed a new product .Your company is a reputed company with 50% market share of same range of products. Your competitors also come with their new products equa
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd