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To Examine the Local Housing Market in a Particular Region

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To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data is given below.
To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data is given below.             For the above data, apply k-means clustering using Price ($) as the variable with k = 3. Be sure to Normalize input data, and specify 50 iterations and 10 random starts in Step 2 of the XLMiner k-Means Clustering procedure. Then create one distinct data set for each of the three resulting clusters of price.  a. For the observations composing the cluster with low home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. b. For the observations composing the cluster with medium home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. c. Comment on the cluster with high home price.
To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data is given below.             For the above data, apply k-means clustering using Price ($) as the variable with k = 3. Be sure to Normalize input data, and specify 50 iterations and 10 random starts in Step 2 of the XLMiner k-Means Clustering procedure. Then create one distinct data set for each of the three resulting clusters of price.  a. For the observations composing the cluster with low home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. b. For the observations composing the cluster with medium home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. c. Comment on the cluster with high home price.
To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data is given below.             For the above data, apply k-means clustering using Price ($) as the variable with k = 3. Be sure to Normalize input data, and specify 50 iterations and 10 random starts in Step 2 of the XLMiner k-Means Clustering procedure. Then create one distinct data set for each of the three resulting clusters of price.  a. For the observations composing the cluster with low home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. b. For the observations composing the cluster with medium home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster. c. Comment on the cluster with high home price.
For the above data, apply k-means clustering using Price ($) as the variable with k = 3. Be sure to Normalize input data, and specify 50 iterations and 10 random starts in Step 2 of the XLMiner k-Means Clustering procedure. Then create one distinct data set for each of the three resulting clusters of price.
a. For the observations composing the cluster with low home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster.
b. For the observations composing the cluster with medium home price, apply hierarchical clustering with Ward's method to form three clusters using Acres and Age as variables. Be sure to Normalize input data in Step 2 of the XLMiner Hierarchical Clustering procedure. Using a PivotTable on the data in HC_Clusters1, report the characteristics of each cluster.
c. Comment on the cluster with high home price.


Definitions:

Male Cone's

Cone-bearing structures on male plants, especially conifers, which produce pollen as part of the reproductive process.

Leaflike Scales

Flattened structures resembling leaves that provide protection or support, often seen in plants or insects.

Sporophylls

Leaves or leaf-like organs of ferns and other similar plants that bear or contain spores.

Female Reproductive Structure

refers to the organs and tissues in female organisms that are involved in producing offspring, including ovaries, fallopian tubes, uterus, and vagina in humans.

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