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The Analysis of Event Attendance Rates

Autor:   •  July 29, 2018  •  Case Study  •  383 Words (2 Pages)  •  92 Views

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Introduction

The analysis of event attendance rates can play a great role in improving the level of preparedness by counties and business for such events.  There is a competitive advantage for event organizers and participants while the local authorities can also benefit by gaining significant insights on facility usage and public planning indicators (Hara et al, 2013). In this paper, an a statistical and graphical analysis of event attendance was done using a series of three critical questions.

The Questions

        The questions that were central to the analysis were as follows:

  1. Which facility has the highest attendance rate?
  2. Which county has the highest attendance rate?
  3. Can we use year to predict attendance rate for the event?

The analysis

  1. Which facility has the highest attendance rate

        The analysis analysis was done using a cumulative histogram and it revealed the following;

        

[pic 1]

        The analysis revealed that Niagra Reservation has the highest level of attendance among the facilities.

  1. Which county has the highest attendance rate?

The analysis for the county with the highest attendance rate. Once again, a cumulative histogram was used to visualize the data.  The result is shown below;

[pic 2]

The analysis revealed that Suffolk county has the highest attendance rate

  1. Can we use year to predict attendance rate for the event?

In order to predict  if the year variable can be used to predict the attendance rate for the events, a regression analysis was carried out and the results found were as follows;

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.023403

R Square

0.000548

Adjusted R Square

0.000244

Standard Error

761634.7

Observations

3296

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

1.05E+12

1.05E+12

1.805054

0.179195

Residual

3294

1.91E+15

5.8E+11

Total

3295

1.91E+15

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

-8627893

6605920

-1.30608

0.191615

-2.2E+07

4324232

-2.2E+07

4324232

Year

4416.591

3287.321

1.343523

0.179195

-2028.81

10861.99

-2028.81

10861.99

...

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