Drip & Dry Data Analysis
The Likelihood of Using the Service Against the Number of Pound per Week
According to Drip & Dry (2014), R-Coefficient of correlation=-0.05779
Having coefficient of correlation, which is equal to -0.05779, means that the two variables are inversely proportional. This means that if one variable increases another decreases. For this case, when pounds of laundry a household increases, the likelihood of using the service decreases.
R-Square= 0.00334
According to MathBits.com (2015), Coefficient of determination measures how well the linear regression line represents data. It also determines the percentage of data that are closed to the linear regression line. So, in this case, 0.334% of the likelihood of using the service can be explained by its relationship with pounds of laundry of a household per week.
The Likelihood of Using the Service Against Customer’s Distance from Drip & Dry
According to Drip & Dry …show more content…
Based on the data analysis, the service that is mostly used is Fold as it has 29.41% of all services provided per week. So, Drip & Dry should take much consideration into this because it is the most source of revenue to the business. When it comes to the number of pound laundry per week, the most laundry used per week is between 11-20Ibs (Drip & Dry, 2014).
Based on data that was provided, Drip & Dry interviewed only 19 people in the whole population of Portland (Drip & Dry, 2014). According to the City-Data.Com (2015), Portland has 33,314 males and 33,004 females. This means that in total, the whole population is equal to 66,318. This means that Drip & Dry only used 0.03% of the whole population. So, Drip & Dry should not base on this data to draw a strong conclusion as it used few people. Then, they need to make sure to use more people in the future study so as to get accurate
The Likelihood of Using the Service Against the Number of Pound per Week
According to Drip & Dry (2014), R-Coefficient of correlation=-0.05779
Having coefficient of correlation, which is equal to -0.05779, means that the two variables are inversely proportional. This means that if one variable increases another decreases. For this case, when pounds of laundry a household increases, the likelihood of using the service decreases.
R-Square= 0.00334
According to MathBits.com (2015), Coefficient of determination measures how well the linear regression line represents data. It also determines the percentage of data that are closed to the linear regression line. So, in this case, 0.334% of the likelihood of using the service can be explained by its relationship with pounds of laundry of a household per week.
The Likelihood of Using the Service Against Customer’s Distance from Drip & Dry
According to Drip & Dry …show more content…
Based on the data analysis, the service that is mostly used is Fold as it has 29.41% of all services provided per week. So, Drip & Dry should take much consideration into this because it is the most source of revenue to the business. When it comes to the number of pound laundry per week, the most laundry used per week is between 11-20Ibs (Drip & Dry, 2014).
Based on data that was provided, Drip & Dry interviewed only 19 people in the whole population of Portland (Drip & Dry, 2014). According to the City-Data.Com (2015), Portland has 33,314 males and 33,004 females. This means that in total, the whole population is equal to 66,318. This means that Drip & Dry only used 0.03% of the whole population. So, Drip & Dry should not base on this data to draw a strong conclusion as it used few people. Then, they need to make sure to use more people in the future study so as to get accurate