You will make a Revenue analysis for Company "Verizon".
Please answer the questions below with detailed explanations. Also, please add a detailed explanation to the 3 pictures I attached.
Please refer to the two samples I attached and Date/Revenue chart.
Autocorrelation Function for Revenue (with 5% significance limits for the autocorrelations) 1.0 D.8 0.6 0.4 0.2 Autocorrelation 0.0 -0.2 -0.4 -0.6 -0.8 -1.0 2 6 8 10 12 14 16 18 20 22 24 26 28 LagRevenue analysis for Company (You can come up with your own title) I. Introduction Company Fiction was founded by First name Last name 1923. It is headquartered in City, State, Country. The company is a major electronic retailer. The purpose of this project is to.... Such analysis is important for the company because it helps... II. Data Description Data used in this analysis are quarterly revenue data from Company Fiction between first quarter of 1999 and last quarter of 2016. There are a total of 80 observations. Below is the summary statistics of the data. Summary Report for Revenue Anderson-Darling Normality Test A-Squared 0.81 P-Value 0.035 Mean 3762 8 561,7 Variance $15472.3 Skewness 0.100407 Kurtosis 0.216371 M 72 Minimum 2278.0 Ist Quartile 3393.3 Median 3715.0 3rd Quartile 1960.8 Maximum 4919.0 2800 3000 3600 4200 95% Confidence Interval for Mean 3630.8 3894.8 95% Confidence Interval for Median 3597.2 3856.3 95% Confidence Interval for StDev 482.6 672.1 95% Confidence Intervals Mea Median 3600 3650 3700 3750 3800 3850 The mean revenue is $3762.8 million with a standard deviation of $561.7 million. The highest revenue is $4919 million in the 4th quarter of 2006 while the lowest revenue is $2278 million in the ist quarter of 1999. We next examine the time series plot and ACF to determine the stationarity of the data.Time Series Plot of Revenue 5000 4500 4000 Revenue 3500 3000 2500 2000 21 28 35 42 49 56 63 Index Based on the plot, we can tell that the company revenue is not stationary. We can observe both an overall upward trend and seasonality. Autocorrelation Function for Revenue (with 5% significance limits for the autocorrelations) LO 0.8 0.6 Autocorrelation -0.2 -04 -0.6 -10 10 12 Lag The ACF further confirms the seasonality observed in the time series plot. The autocorrelation for the 4th, 8th and 12th lags are significant.Summary Report for Revenue Anderson-Darling Normality Test A-Squared 3.64 P-Value
