Business Forecasting

Second determine if this new regression equation is statistically significant. Is this new regression equation with the independent variables, chosen with the stepwise statistically significant? Use the multi-step hypothesis test for

Target is the second biggest retail company after Walmart. Native New Yorker, George Draper Dayton first built a company named Dayton Dry Goods Company in 1902 in the Minneapolis area which is now known as target headquarter. Walmart faced the out of stock issue problem last year and now their biggest competitor, Target, also has faced the same problem this year. Target has a problem keeping the availability of the product in their stores in Canada. It resulted in a huge loss of money and closing down their stores. The CEO of Target said that this is a serious problem and must been solved.

results from the model were both accurate and reliable. The multiple R and the R

5) Graph the equation you wrote in step four superimposed over the original data. Comment on how well or how poorly the equation fits the data.

Referring to Figure 6.2.3 and 6.3.3, it was proven that our model has problems that the sample data used does not represent the whole population. Therefore, this is one of the flaws in our research. A more constructive suggestion to eliminate this problem would be to extend the research with a larger sample size with longer time horizon. And if the sample size is large enough, the time series issue can be neglected.

Model Fit Summary CMIN Model | NPAR | CMIN | DF | P | CMIN/DF | Saturated model | 36 | .000 | 0 | | | Independence model | 8 | 3797.971 | 28 | .000 | 135.642 | RMR, GFI Model | RMR | GFI | AGFI | PGFI | Saturated model | .000 | 1.000 | | |

This paper comprises an appreciation of data representation, its visualization, an outline description of behavior, plus an indication of the use of the equation in engineering.

For the first part of the lab, our goal was to calculate the time constant, , of an RC circuit. We made an RC series circuit and connected it to the Rigol wave generator to produce a square waveform for current. Then, we collected data of the voltage across the capacitor at different points in time using a myDAQ and the 4BL application. In order to find the time constant, we linearized the voltage we measured across the capacitor and then performed a linear regression on the data. The equation for the voltage across the capacitor as a function of time is:

In order for me to find the appropriate model I need to evaluate them by using ln(Y) and Ŷ calculations. I analyzed the Linear: Ŷ= 10.4446 + .755 R2= .9719 , squared: Ŷ= 11.31 + .5951(x1) + .0062(x12) R2= .9745 , cubic: Ŷ= 12.0508 + .3627 (x1) + .0264(x12) - .00051 (x13) R2= .9751 , log log: ln(Y)= exp(2.0403 + ln(x1) + (.0597/2)^2 R2=.9072 , logarithmic: Ŷ = 2.1503 + ln(x1) R2= .8523 , and exponential: ln(Y) = exp(2.4924 + .0383(x1) + (.0375/2)^2 R2= .9634. After analyzing the R2’s I narrowed it down to Cubic. Cubic has the highest R2 and is the most promising of the models. Based on my results from (b) and (c) also regards to how I achieved Mileage Cubic to be the best

1. In this sim, what variables are you seeing? Write the formula below, and indicate the units used to measure each one.

Calculate the exponential smoothing forecast + trend for week2 using an alpha of 0.30, delta of 0.20, FITt-1 of 5400, Tt-1 of 200 and At-1 of 5600

Forecasting is the methodology utilized in the translation of past experiences in an estimation of the future. The German market presents challenges for forecasting techniques especially for its retail segment. Commercially oriented organizations are used to help during forecasting as general works done by academic scientists are not easy to come across (Bonner, 2009).

Phase 4 - Model/Design/Development: depend on the problem area, data maturity and the expected benefits from the predictive model in the data science project, the analytical modeling method will be chosen. Analytical modeling includes descriptive, predictive, and prescriptive analysis using machine learning algorithms such as regression, clustering, or classification.

Business analytics, in a nutshell, is usage of the type of data that can help one analyze a particular business situation and decide how to improve it. Instruments used for such an assessment include statistics, and both quantitative and qualitative analysis, as well as predictive and explanatory modeling.

QUESTION: What are the forecasting needs of a seasoned idea start-up and a new idea start up?