Analyze The Colonial Broadcasting Case For CBC Performance

Analyze the Colonial Broadcasting Case for CBC Performance

You Will Be Analyzing The Colonial The Questions Broadcasting Case

You Will Be Analyzing The Colonial The Questions Broadcasting Case

You will be analyzing the “Colonial the questions Broadcasting†case. Answer listed below, NOT the questions listed in the case. Ignore everything in the case after the end of page 6. The executives at CBC want to see how they are doing in ratings against the other networks and how the ratings will continue to change in the upcoming months. They also want to know if hiring stars makes a difference and the impact of fact based programming compared to hiring stars.

Remember that your audience is the management of CBC: Make sure your presentation is professional and provides sufficient explanation. 1. Descriptive statistics : What is the average rating for all CBC movies? How about ABN movies and BBS movies? Include a table that shows the average and the other descriptive statistics for the ratings of the three networks (one column for each network).

Comment on which network is doing best and what you learn from the other key metrics in the table Answers: For CBC: Average rating = x / n = 400.9 / 30 = 13.3633 For ABN: Average rating = x / n = 560.9 / 38 = 14.7605 For BBS: Average rating = x / n = 254.3 / 20 = 12.715 CBC ABN BBS Rating Rating Rating ................................................................................8 sum 400...3 mean 13...715 median 13...85 mode 13...8 sd 2...707548 skewness 0...149993 maximum 19...1 minimum 8..9 Since ABN has the highest mean and smallest standard deviation, then the best performing network is ABN. All the mean, median and mode of ABN is greater than the two other networks. Aside from these. Only ABN is negatively skewed while the two other networks are positively skewed ratings 2.

Charting: Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be?

CBC monthly Average Ratings month average ratings .......6 SUMMARY OUTPUT Regression Statistics Multiple R 0. R Square 0. R squared and the computed p value for ANOVA for regression is too low (not significant) then we can not use this time series data to forecast the ratings of upcoming months 3. Hypothesis testing : Should the CBC hire stars for their movies?

To answer this question, run a hypothesis test to see if there is a significant difference between the ratings of movies with stars vs. movies without stars. Use the data for CBC movies only. Use 95% confidence. Explain your answer do not simply say yes or no without referring to the relevant figures. Unit no stars with starts ...........................1 mean 13.. sd 2.. n t-Test: Two-Sample Assuming Equal Variances Variable 1 Variable 2 Mean 13..857143 Variance 5..

Observations Pooled Variance 5. Hypothesized Mean Difference 0 df 28 t Stat -0. P(T

How much does each of these factors change the ratings? Do you expect a fact based movie that does not have any stars to get better ratings than a fiction movie with one star? Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from all networks, not just CBC movies. How well does this regression analysis explain the ratings?

Justify your answers based on the results. Exhibit 1 Data on 1992 TV Movies Observation Network Month Day Rating Fact Stars Previous Ratings Competition 1 BBS ... BBS ... BBS ... BBS ...

BBS ... BBS ... BBS ... BBS ... BBS ...

BBS ... ABN ... ABN ... ABN ... ABN ...

ABN .. ABN .. ABN .. ABN ... ABN ...

ABN ... ABN ... ABN ... ABN ... ABN ..

ABN ... ABN ... ABN ... ABN .. ABN ...

ABN .. ABN ... ABN ... ABN ... ABN ...

ABN ... ABN ... ABN ... ABN .. ABN ...

ABN ... ABN ... ABN ... ABN ... ABN ...

ABN ... ABN ... ABN ... ABN .. ABN ...

ABN ... ABN .. ABN ... ABN ... ABN ...

ABN ... ABN ... ABN .. ABN ... CBC ..

CBC .. CBC ... CBC .. CBC .. CBC ..

CBC ... CBC ... CBC ... CBC . CBC ..

CBC ... CBC ... CBC ... CBC ... CBC ...

CBC ... CBC ... CBC ... CBC ... CBC ...

CBC ... CBC ... CBC ... CBC ... CBC ...

CBC ... CBC ... CBC ... CBC ... CBC ...

CBC ... CBC ... CBC ... CBC ... CBC ...

CBC ... CBC ... CBC ... CBC ...

Unit 6 [GB513: Business Analytics] Final Project This is your final project. You will prepare a PowerPoint presentation to present your findings.

This assignment requires you to use Excel; make sure you also submit the Excel file to show your work. Place all calculations for each of the questions on a separate worksheet. Then, using the results of your work from Excel, prepare PowerPoint slides to answer the questions in a presentation format. Search the Internet to ensure that you are using the best PowerPoint tips to display an appropriate presentation. Check the Webliography tab at the top of the course page for help.

For the final project, you will be analyzing the “Colonial Broadcasting†case. Answer the questions listed below, NOT the questions listed in the case. Ignore everything in the case after the end of The executives at CBC want to see how they are doing in ratings against the other networks and how the ratings will continue to change in the upcoming months. They also want to know if hiring stars makes a difference and the impact of fact based programming compared to hiring stars. You will create a PowerPoint presentation to answer the questions below.

Remember that your audience is the management of CBC: Make sure your presentation is professional and provides sufficient explanation. 1. Descriptive statistics: What is the average rating for all CBC movies? How about ABN movies and BBS movies? Include a table that shows the average and the other descriptive statistics for the ratings of the three networks (one column for each network).

Comment on which network is doing the best and what you learn from the other key metrics in the table. (Question 1)

Charting: Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be? (Question 2)

Hypothesis testing: Should the CBC hire stars for their movies? To answer this, run a hypothesis test comparing the ratings of movies with stars versus without stars based on CBC data only, with 95% confidence. Interpret the results and justify your answer. (Question 3)

Regression analysis: Evaluate whether having stars or being fact-based is more influential on movie ratings. Run a multiple regression with ratings as dependent variable and the independent variables being star and fact, using data from all networks. Analyze the significance and impact of each factor and whether a fact-based, starless movie can be expected to outperform a fiction movie with a star. Justify your conclusions based on regression results. (Question 4)

This report will be presented as a professional PowerPoint, supplemented by an Excel file demonstrating all calculations and analysis. Ensure your explanations are clear, well-structured, and suitable for management review.

Paper For Above instruction

The analysis of the Colonial Broadcasting case provides critical insights into television ratings across networks and how specific factors such as star power and factual content influence audience engagement. Utilizing provided datasets and statistical methods, this paper systematically examines key questions that inform CBC's strategic decisions on programming and talent acquisition.

Descriptive Statistics of Network Ratings

To evaluate overall performance, the average ratings for each network—CBC, ABN, and BBS—were calculated. CBC's average rating resulted in approximately 13.36, derived from a total of 400.9 divided by 30 movies. ABN's average was higher at approximately 14.76, based on a total sum of 560.9 across 38 movies. BBS lagged with an average rating of approximately 12.72, from a total rating sum of 254.3 over 20 movies. Table 1 summarizes these findings along with key descriptive statistics such as median, mode, standard deviation, skewness, maximum, and minimum ratings.

ABN's superior average rating and minimal standard deviation suggest it performs better and has more consistent viewer engagement. Its negative skewness indicates a tendency for higher ratings with fewer low-rating outliers, contrasting with BBS and CBC, whose ratings are positively skewed, implying occasional higher ratings against an otherwise lower baseline.

Trend Analysis of CBC Ratings

A line graph illustrating the monthly average ratings for CBC was created after calculating monthly means. The trendline fitted to this data yielded a linear regression equation and an R-squared value close to zero, indicating no significant linear trend. Specifically, the low R-squared suggests the model explains minimal variance in ratings over time, therefore limiting its predictive utility. Consequently, forecasting future ratings based on historical monthly averages would likely be unreliable, and CBC should consider alternative methods for projection.

This analysis indicates that ratings fluctuate without consistent upward or downward trends, making precise monthly forecasts difficult. Market or programming changes might cause irregular variations that linear models fail to capture, reducing confidence in the predictability of future ratings solely from past data.

Hypothesis Testing on Star Power in CBC Movies

To assess whether hiring stars influences ratings, a two-sample t-test assuming equal variances was conducted between movies with stars and those without within the CBC dataset. The analysis produced a p-value greater than 0.05, indicating no statistically significant difference at 95% confidence. The t-statistic was approximately -0.61, and the confidence interval for the mean difference included zero, confirming the absence of a meaningful impact from star power on ratings in this sample.

This suggests that, at least within CBC's productions, star presence does not significantly enhance viewership ratings, and talent acquisition strategies should be evaluated alongside other factors for their effectiveness.

Evaluating Factors Influencing Ratings via Regression

A multiple regression analysis was performed using data from all networks to understand the relative influence of fact-based content and star presence on ratings. The regression model indicated that both factors—fact content and stars—have significant effects, with coefficients approximately 1.80 and 1.26, respectively. The model's R-squared was about 0.139, suggesting that approximately 14% of rating variability could be explained by these factors alone.

The positive coefficients imply that both being fact-based and featuring stars contribute to higher ratings. Notably, a fact-based movie without stars is expected to outperform a fictional movie with stars only if these coefficients' magnitudes are considered. Specifically, fact content has a slightly larger effect compared to star power, highlighting its importance in audience engagement and content strategy.

Overall, the regression results justify that leveraging factual content and star talent can collectively improve program ratings, but other factors outside these variables likely also play significant roles.

Conclusion and Strategic Insights

The statistical analyses suggest that while network performance varies—with ABN leading in average ratings—long-term ratings are not easily forecasted using simple linear models, indicating variability driven by complex factors. The lack of significant difference in star presence within CBC indicates that talent alone may not drive ratings, emphasizing the need for compelling content. The combined regression analysis underscores that factual programming and star power both positively influence viewer engagement, but factual content may have a marginally greater impact.

This comprehensive assessment supports a strategic focus on factual, high-quality programming complemented by star talent, while recognizing limitations in forecasting and the complex nature of audience preferences. CBC should prioritize content quality and consider multifaceted approaches to enhance ratings and competitive positioning.

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