Summarizing & Presenting Data
The housing market changes quite frequently and depending on the city, state, and neighborhood. When a home-buyer is interested in purchasing a home they look for what fits their needs, life style, and budget. This is important because it will also determine what type of house they can afford to live in and how much they can get for the amount their budget will allow. Buyers and sellers will look for certain variables when purchasing or selling a home and data must be gathered to make sure that all details match and that all requirements are met. It would be safe to assume that our theory that the larger the house and the more rooms a house has, the more expensive the price of the house will be. The three major variables in our data summary are: number of bedrooms, size of the house, and number of baths.
According to our information compiled (see attached excel file for mega stat), the measure of tendency that best represents the data set is the median because the variability of the data is less between mean and mode data set. In addition, the outlier is less between mean and mode.
VARIABLES MEAN MEDIAN MODE
Bedrooms 3.80 4.00 4.00
Size 2,223.81 2,200 2,100
Baths 2.081 2.00 2.00
According to our computation for measure of dispersion (see attached excel file for mega stat), we found out that there are low and high outliers that existed on one of the variable. Under the size of the house column, the low outlier shows 1 deviation and 3 deviations on high outlier. It means that there is variability in the measurement or possibly, an error on the data gathered.
VARIABLES STANDARD DEVIATION SAMPLE VARIANCE SKEWNESS COEFFICIENT OF VARIATION
Bedrooms 1.50 2.26 .66 39.54%
Size 248.66 61,831.50 .32 11.18%
Baths .393 .154 .794 18.89%
The appropriate bivariate chart to use in this scenario is the scatter gram which is defined as a two-dimensional plot, with one variable’s values plotted along the horizontal axis and the other along the vertical
According to our information compiled (see attached excel file for mega stat), the measure of tendency that best represents the data set is the median because the variability of the data is less between mean and mode data set. In addition, the outlier is less between mean and mode.
VARIABLES MEAN MEDIAN MODE
Bedrooms 3.80 4.00 4.00
Size 2,223.81 2,200 2,100
Baths 2.081 2.00 2.00
According to our computation for measure of dispersion (see attached excel file for mega stat), we found out that there are low and high outliers that existed on one of the variable. Under the size of the house column, the low outlier shows 1 deviation and 3 deviations on high outlier. It means that there is variability in the measurement or possibly, an error on the data gathered.
VARIABLES STANDARD DEVIATION SAMPLE VARIANCE SKEWNESS COEFFICIENT OF VARIATION
Bedrooms 1.50 2.26 .66 39.54%
Size 248.66 61,831.50 .32 11.18%
Baths .393 .154 .794 18.89%
The appropriate bivariate chart to use in this scenario is the scatter gram which is defined as a two-dimensional plot, with one variable’s values plotted along the horizontal axis and the other along the vertical