Logistic Regression Case Solution And Analysis, HBR Case Study Solution & Analysis of Harvard Case Studies

Logistic Regression The case solution

Data Description

The variables included in the regression, are defined as below

no_of_adults: Number of adults
no_of_children: Number of Children
no_of_weekend_nights: Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel
no_of_week_nights: Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel
type_of_meal_plan: Type of meal plan booked by the customer:
- Not Selected – No meal plan selected
- Meal Plan 1 – Breakfast
- Meal Plan 2 – Half board (breakfast and one other meal)
- Meal Plan 3 – Full board (breakfast, lunch, and dinner)
required_car_parking_space: Does the customer require a car parking space? (0 - No, 1- Yes)
room_type_reserved: Type of room reserved by the customer. The values are ciphered (encoded) by Star Hotels Group
lead_time: Number of days between the date of booking and the arrival date
arrival_year: Year of arrival date
arrival_month: Month of arrival date
arrival_date: Date of the month
market_segment_type: Market segment designation.
repeated_guest: Is the customer a repeated guest? (0 - No, 1- Yes)
no_of_previous_cancellations: Number of previous bookings that were canceled by the customer prior to the current booking
no_of_previous_bookings_not_canceled: Number of previous bookings not canceled by the customer prior to the current booking
avg_price_per_room: Average price per day of the reservation; prices of the rooms are dynamic. (in euros)
no_of_special_requests: Total number of special requests made by the customer (e.g. high floor, view from the room, etc)
booking_status: Flag indicating if the booking was canceled or not.
Data Analysis
In order to determine the data structure, the top ten rows were selected, which are as follows

As shown below, the data type has been identified for the complete data set, which shows the “object” type data for our key variable i.e. cancelation status. The object type data has been arranged into integer type data i.e. “1 for Cancelled” and “0 for Not-cancelled”.
Descriptive Analysis

The descriptive statistics of the variables are given as below. The descriptive statistics show that the mean number of adults are 1.87, mean number of children 0.11, mean number week end nights 0.83, mean booking status of 0.387 etc. Further descriptive statistics, show the minimum, maximum and standard deviation values, which are given as under
Univariate Analysis

In univariate analysis, univariate descriptive have been calculated for each variable, whereby, the impact of one independent variable over the dependent variable i.e. “booking status” are observed. The mean, minimum, maximum and standard deviation values for each variable are describe above in the descriptive statistics. The frequency of independent variables are shown through histograms, as given below
...............................
This is just a sample partial case solution. Please place the order on the website to order your own originally done case solution.