Condominiums for Sale
The cost or real estate can differ from region to region and with size and quality. One factor that greatly effects the sale of a piece of property with a view. Such is the data that will be analyzed herein. Can the data support the fact that there will be buyers willing to pay more for a condominium with a view? Consequently, would a comparable home without a view that is considerably less expensive actually take longer to sell?
Overview of the Condominiums for sale The data analyzed below in Table I, clearly depicts the fact that the condominiums with a view are selling for more than half the price of one with a view. It also indicates that the units are selling on average, 50 days sooner too. In fact, one of the …show more content…
The list price for a gulf view ranges from 161K to a staggering 996K. The 996K condominium is also considered an outlier and will skew the data negatively until sold or brought down closer to the mean list price. This is in stark contrast to the range in price for a non-gulf view home which is more consistent with a minimum value of 130K and a max value of 212K. This measurement of variability is simple. In fact, Anderson, Sweeney, Williams, Camm, and Cochrane (2015) stated that the range is “the simplest measure of variability” (p. 122). It is as simple as subtracting the maximum home price from the minimum home price in the same category. For instance, if one noted the data in Table II and subtracted the minimum gulf view listed price of 161K from the gulf view maximum listed price of 996K, he or she would get a range of …show more content…
In fact, Anderson et al. (2015), stated that “the value .95 is referred to as the confidence coefficient, and the interval 78.08 to 85.92 is called the 95% confidence interval” (p. 340). This should express that a normal distribution will always follow this rule. Therefore, if one wanted to ensure that home sales were still tracking to normal distribution, a quick calculation would ensure it. If home sales or prices experienced an unusual circumstance, this calculation would allow one to see if the data were skewing positively or negatively. It is clear from the data in Table II that all four of the calculations are tracking to a normal distribution and all data points are within the 95% confidence
The cost or real estate can differ from region to region and with size and quality. One factor that greatly effects the sale of a piece of property with a view. Such is the data that will be analyzed herein. Can the data support the fact that there will be buyers willing to pay more for a condominium with a view? Consequently, would a comparable home without a view that is considerably less expensive actually take longer to sell?
Overview of the Condominiums for sale The data analyzed below in Table I, clearly depicts the fact that the condominiums with a view are selling for more than half the price of one with a view. It also indicates that the units are selling on average, 50 days sooner too. In fact, one of the …show more content…
The list price for a gulf view ranges from 161K to a staggering 996K. The 996K condominium is also considered an outlier and will skew the data negatively until sold or brought down closer to the mean list price. This is in stark contrast to the range in price for a non-gulf view home which is more consistent with a minimum value of 130K and a max value of 212K. This measurement of variability is simple. In fact, Anderson, Sweeney, Williams, Camm, and Cochrane (2015) stated that the range is “the simplest measure of variability” (p. 122). It is as simple as subtracting the maximum home price from the minimum home price in the same category. For instance, if one noted the data in Table II and subtracted the minimum gulf view listed price of 161K from the gulf view maximum listed price of 996K, he or she would get a range of …show more content…
In fact, Anderson et al. (2015), stated that “the value .95 is referred to as the confidence coefficient, and the interval 78.08 to 85.92 is called the 95% confidence interval” (p. 340). This should express that a normal distribution will always follow this rule. Therefore, if one wanted to ensure that home sales were still tracking to normal distribution, a quick calculation would ensure it. If home sales or prices experienced an unusual circumstance, this calculation would allow one to see if the data were skewing positively or negatively. It is clear from the data in Table II that all four of the calculations are tracking to a normal distribution and all data points are within the 95% confidence