Descriptive statistics

What is descriptive statistics? Usually under descriptive statistics summative methods of description the data in succinct ways is considered. Data analysis usually begin with descriptive statistics, because it helps to understand what data we have – what is the sample, what is the accuracy of the data and how it is possible manage it.

The analysis of data usually begins with such descriptive statistics as the mean, median, mode, variance and standard deviation. Mean, median, and mode are known as measurements of the central tendency of the data and range, standard deviation, variance give the information about the variability of the data. The mode should be preferably used when calculating measure of center for the*…show more content…*

Variable names are:

PRICE = Selling price ($ hundreds)

SQFT = Square feet of living space

AGE = Age of home (years)

FEATS = Number out of 11 features (dishwasher, refrigerator, microwave, disposer, washer, intercom, skylight(s), compactor, dryer, handicap fit, cable TV access

NE = Located in northeast sector of city (1) or not (0)

COR = Corner location (1) or not (0)

TAX = Annual taxes ($)

Where variables “Age” and “Tax” have missing values. In this work I will not touch the question of missing data management techniques, because it is different and very broad topic. And for the simplicity reasons I will delete cases with missing values for the variable “Age” from the analysis, and not use variable “Tax” for the further analysis.

Cleared data file consists of 68 cases (see appendix 1).

Mean

The mean of a data set is the arithmetical average of all the numbers. Its formula is:

where n is number of cases.

One problem with using the mean, is that if there is one outcome that is very far from the rest of the data (outlier), then the mean will be strongly affected by this outcome. There is possibility to low down the effect of outliers. This method is called the trimmed mean. The idea of the trimmed mean is to get rid of the outliers or 5% on the top and 5% on the

What is descriptive statistics? Usually under descriptive statistics summative methods of description the data in succinct ways is considered. Data analysis usually begin with descriptive statistics, because it helps to understand what data we have – what is the sample, what is the accuracy of the data and how it is possible manage it.

The analysis of data usually begins with such descriptive statistics as the mean, median, mode, variance and standard deviation. Mean, median, and mode are known as measurements of the central tendency of the data and range, standard deviation, variance give the information about the variability of the data. The mode should be preferably used when calculating measure of center for the

Variable names are:

PRICE = Selling price ($ hundreds)

SQFT = Square feet of living space

AGE = Age of home (years)

FEATS = Number out of 11 features (dishwasher, refrigerator, microwave, disposer, washer, intercom, skylight(s), compactor, dryer, handicap fit, cable TV access

NE = Located in northeast sector of city (1) or not (0)

COR = Corner location (1) or not (0)

TAX = Annual taxes ($)

Where variables “Age” and “Tax” have missing values. In this work I will not touch the question of missing data management techniques, because it is different and very broad topic. And for the simplicity reasons I will delete cases with missing values for the variable “Age” from the analysis, and not use variable “Tax” for the further analysis.

Cleared data file consists of 68 cases (see appendix 1).

Mean

The mean of a data set is the arithmetical average of all the numbers. Its formula is:

where n is number of cases.

One problem with using the mean, is that if there is one outcome that is very far from the rest of the data (outlier), then the mean will be strongly affected by this outcome. There is possibility to low down the effect of outliers. This method is called the trimmed mean. The idea of the trimmed mean is to get rid of the outliers or 5% on the top and 5% on the

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