Karen Payne, owner of the Vintage restaurant in Ft. Myers, Florida is looking to predict future food and beverages sales with their current sale history. The Vintage restaurant, a high-quality establishment, has just completed its third year in operation and provided us with their monthly food and beverage sales. Upon initial analyzation of our data, we could easily tell that there was a seasonality trend in the data provided to us. Some additional statistics about the data follow:
• September was the lowest month of sales (each year)
• December was the highest grossing month of sales (each year)
• From Sept. to January, sales would grow (each year)
• From January to Sept., sales would decline (each year)
With this in mind, I then began
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With that coefficient irrelevant, the numbers of the above coefficients are slightly different to provide an adjusted forecasting model.
According to the data above, forecasted sales (in thousands) equals 223.667 + the correlating coefficient depending upon the month of the forecast. Furthermore, this indicates that before the business was opened, they were earning $223.667(thousand). Obviously, did not happen so we can disregard this value due to extrapolation.
With this regression we were also provided an R squared value of .948 or 94.8% meaning that 94.8% of the variability in food and beverage sales can be explained by the month coefficient.
With two indicators now showing that the model with a trend is providing more accurate results (graph and the R-squared value), I felt slightly more confident in using that forecasting model. To be completely sure however, I decided to verify with one more test: the mean squared error. The mean squared error measures the average of the squares of errors, - the lower the MSE, the better. Overall, the mean squared error for our data with a trend was 12.6 indicating that the model closely resembles the data that we were provided. For our linear regression model without a trend, the MSE was calculated at 111.96 indicating that the model is not as closely related to
In a simple regression model, we are trying to determine if a variable Y is linearly dependent on variable X. That is, whenever X changes, Y also changes linearly. A linear relationship is a straight line relationship. In the form of an equation, this relationship can be expressed as
regression of y on x, the power transformation model has a higher R^2 which is .
Lucilles American Cafe is located in Weston, Florida. Weston is located just west of Fort Lauderdale. Weston is a suburban community established since 1996. The city is located thirty minutes west of the beach. Weston’s employment rate is about 3.89%, being ranked as the city with the largest job growth in Florida as well as 18th in the nation. Weston is the westmost city in Broward County, it has a population of over 65,000 (2010 census). Not only is Weston a great location to have restaurants because of its high increasing population, its family friendly environment also helps. Being named by Family circle magazine as one of the Ten Best Towns for Families in 2015, Weston has a enormous number of family orientated activities and events.
Teens being discriminated for being loud? Aren’t adults noisy themselves? Munchy’s restaurant should not ban students, when adults are also loud. Munchy’s is now creating a “quiet lunch” for adults that ban students for certain hours.
As an add-on component to its IT Operations-as-a-Service program for Whataburger Restaurants, Sigma offers the SmartHands Dispatch service for the onsite support at Whataburger stores. Dispatch services may be delivered by Sigma employees or an approved 3rd party managed by Sigma. The scheduling and deployment of a technician will occur after the Sigma ITOaaS Operations team has provided remote support and troubleshooting as part of the MANAGED Service Level support agreement.
I chose four different local restaurants of Wheeling, WV. These particular four restaurants had similar ratings and are well known by many people. Often, these four restaurants can be among the favorite restaurants of many people. Therefore, I wanted to evaluate them against my criteria to see which restaurant is actually the best.
The restaurant I went to was Cactus, they serve Mexican cuisine. It is located on Gilbert Street in Iowa city. I have been to this restaurant a few times prior to this assignment. The reason I decided to go to Cactus was because I love Mexican food. Another reason why I went there was because when I asked upper classman of a good Mexican restaurant in Iowa City, they all recommended Cactus.
After we completed the three regressions in total, we then evaluated the differences and determined which model out of the three would be the best. Between the three regression models that were completed, Model #3 would be the best model. The reason Model #3 is the best model out of all of them is due to the increase in the adjusted R2, which ended up being the highest out of all of the regressions that we ran according to the regression statistics. Model #3 consists of the data that includes the purchase amount by gender, controlling for the age of the customer, and the day of the week the purchase was made. The Adjusted R2 was higher than the other models due to the fact that the regression in Model #3 took more variables into
Based the principle that easy and friendly to apply this model in practice to forecast C1 product of MAD Ltd, especially provide information for the people that don’t equipped with any skills on VBA and forecasting knowledge. This model using solver, Holt-Winters forecasting method and VBA to achieve automatically calculation to obtain the result of next quarter or next whole year forecast.
There are thousands of different restaurants around the globe where people can either wait five minutes for their lunch in a drive-thru lane but pay for rude service and processed food, and some where formal attire is required and food and beverages are so expensive they break the bank. But what if there was a restaurant that offered both? A restaurant where service is top-of- the-line, food is warm and fresh, and the setting is elegant but inexpensive? A restaurant like this is not easy to find but thankfully, it does exist. The highly popular and many-favorited Italian restaurant, Olive Garden is the place to be. Opened on December 13th, 1982, in Orlando, Florida, Olive Garden quickly became the fastest-growing Italian-themed restaurant in
The next model is the Quadratic Trend Model. The quadratic formula uses the least-squares method to forecast and can be written as Yi =b_0+ b_1 X_1+ b_2 X_2. In this formula the only difference is b_2 X_2 represents the estimated quadratic effect on Y. Figure 1-6 represents the comparison between the linear and quadratic
b. To show the proportion of your budget spent on each of the four fixed costs for your company during the year.
It is undetermined in being able to use the forecast method due to the fact that there is not data to compare it to. Furthermore, in this case, there cannot be any ramification to the inventory that can be identified.
Business forecasting can be used in a wide variety of contexts, and by a wide variety of businesses. For example, effective forecasting can determine sales based on attendance at a trade show, or the customer demand for products and services (Business and Economic Forecasting, p.1). One of the most important assumptions of business forecasters is that the past acts as an important guide for the future. It is important to note that forecasters must consider a number of new information, including rapidly changing economic conditions and globalization, when creating business forecasts based on past sales.
The newer steer’s stores are built so that customers can see the kitchen where food is made. This creates transparency and interaction with staff and allows customers a glimpse of behind the scenes