Just 2 Questions... 1. Forecasting techniques rely on the adage that history repeats itself. Many times, though, it has been noted that there is no guarantee that historical patterns will repeat and, even if they do, it can be difficult or impossible to predict when a pattern will repeat itself. Provide two time series examples that seemed stable and predictable until there was a significant change to the pattern. Was there a way to predict the pattern change? Explain. 2. Technically, once a time series model is built, any future value can be forecasted. For example, assume you built a model that forecasts monthly sales of a product given the last 3 months of sales. Using the model, you forecasted monthly sales for the next 6 months, and the model provided very accurate predicted sales.Your manager wants to use your model to predict sales for the next 5 years. What are some problems that could occur with extending the forecast horizon out that far? How would this affect your confidence in the forecasted values for a year? Five years? Explain.

Web page scraping is a common way to collect data and search for particular items. Use R to capture the content of a job listing website of your choice such as Monster.com, Indeed.com, or any other relevant job listing website. Using R, capture the data for the postings that relate to cybersecurity for the last 30 days. In R, identify the frequency of the job listings that contain specific requirements for the CISSP® certification and the years of required experience.In a Word document, clearly identify the site you scraped. Paste the R code you created to acquire, and identify the information relevant to the cybersecurity listings you identified from the site. Include a screen capture or other form of visual in the Word document that demonstrates the results of your R code. Submit the document to Waypoint for grading.In your Word document,Summarize the results for the elements you acquired from the job site. Be sure to identify the website scraped.Include the R code you developed to acquire and identify the data.Demonstrate the results of the R code for the job elements identified by including a screen capture of the data.The Web Page Scraping With R paperMust include a separate title page with the following:Title of AssignmentStudent’s nameCourse name and numberInstructor’s nameDate submitted

In this task, we are going to write a program test7.py that finds the roots of cubic polynomials listed in the file poly.txt using goalSeek function. 1. Use goalseek function to find the roots of the polynomials P1, P2, p3 listed in the introduction. The expected answers are: 3, 1.5, and -4.2. Choose the limits to contain the roots you are looking for (-5 and 5 would suffice for these there polynomials). Confirm that your programs is finding correct roots. 2. Read the file poly.txt. Discard any line that starts with a # symbol ( thus skipping the header).for each non-header line, split it and use float function to extract A, B, C, D, Lo, Hi. Print them out to confirm that your program correctly extracts these parameters. 3. Write function makePoly that can generate a python function representation of cubic polynomial from its coefficients A, B, C, D. For example, the polynomial function P1 we used earlier: def P1(x): return x*x*x - x* + 4*x - 30could be created with the generator function as follows: P1 = makePoly(1, -1, 4, -30)