Real Estate Market Analysis Coursework

Real Estate Market Analysis
Student’s Name
Institutional Affiliation
Real Estate Market Analysis
15 1/ Summarize and describe the data for someone who knows a lot about the residential real estate industry but who is not familiar with the rental market in Guelph. Please note at least six different facts that make the Guelph data special (including one fact presented in a graphical format). For each, include a short comment showing how that fact is relevant to decision making. (Use Guelph Rental Data 2019)
The Guelph Rental Data 2019 contains 83 observations, where each has 17 variables. The variables are:
* ID: Becomes more useful in lots of small ways after you become more experienced.
* Rent per month (in $): Likely to be the variable (yield in the regression equation) you want to explain.
* Bedrooms: As if the units may not have enough space to include more than one bedroom.
* Bathroom: As if the units are identical with a lavatory or two.
* Size: As if all units have different sizes.
* Walk score overall: As if all units differ in the overall rating.
* Travel time: Usual variation in location results to variation in travel time.
* Style of unit: As if all entities differ in styling.
* Floor level: As if these units are identical but on different floors.
* Utilities included: As if all units may (not) have services.
* Heating: As if the units differ in heat.
* Amenities flooring: As if all units may (not) have a carpet.
* Amenities laundry: As if all units may (not) have a laundry machine.
* Amenities parking included: As if some units may not have parking space due to variation in size of the entity.
* Grocery, how far in km? : Usual variation in distance from the grocery store.
* Appliances dishwasher: As if all units may (not) have a dishwasher.
* Well furnished: As if all units may (not) have the required equipment.
Forward sorting: As if all units differ, thus forward sorting.
Latitude: Actual latitude position on a map as if the city hall is at 0’0.
Longitude: Actual longitude position on a map as if the city hall is at 0’0.
Among these facts on Guelph data listed above, at least six different circumstances that make the Guelph data special. These include forward sorting, latitude, longitude, style of unit, amenities (ex) inclusion, walk score overall, and furnished.
(45) 2. Which regression equation explains the data on monthly rent best? Be sure to discuss why you included some variables in the regression equation and why you excluded some. (Copy and paste your regression table into your report.) (Use Guelph Rental Data).
The assumption used in this implementation is that the rent ($ per month) is expected to equal a0+ a1*x1 + a2*x2 +a3*x3+a4*x4+a5*x5= Y which is (rent ($ per month)) where; everything but a0, a1, a2, a3, a4, and a5 represents bedrooms, walk score, size per sq. Ft., furnished, and travel time. The goal of the implementation is to estimate a0, a1, a2, a3, a4, and a5. The chosen variables are crucial for real estate personnel and potential clients. For example, prospective clients tend to enquire about the number of bedrooms in a unit they want to rent. Those with large families may opt to choose one with more than four bedrooms and one bathroom since it’s spacious. I chose travel time to UG because most clients are likely to be students, lecturers, and workers.
Conversely, the variables excluded were termed less significant for inclusion in the equation due to existence of substitution. For instance, amenities such as parking availability can be foregone or substituted in the case where a client does not own a vehicle or chooses to use cab services during their stay there. Generally, the price of a unit is usually determined by the number of bedrooms, walk score overall, size per Sq. Ft., furnished or not, and travel time.
Therefore, the regression equation is as follows:
Rent ($ per month) = 1169.4267+292.3017#Bedrooms-0.1647Size (Sq.Ft)-2.0425Walkscore (overall) +11.5821Travel Time to UG -58.54440Furnished
The excel regression output of the above equation is:
PS NOTE:
The Y or N answers in the furnished variable replaced the 1 and 0, respectively, as the Excel Regression function requires numerical values in the X and Y data. And N/A into 0.
20 3/ a) Predict the monthly rent price of a unit described by the following variables: (use Guelph Rental Data 2019, Step by Step Instruction 2019 & Multivariate Estimate)
Two bedrooms and one bathroom
Located in the Forward Sorting Area N1H
With utilities included and

With parking included.
If this list omits any characteristic that you think is important, then choose a reasonable value of that characteristic, state it as a planning assumption and u...