Descriptive and Predictive Analysis of Eclipse Vans

The following study seeks to exhibit the descriptive statistics of Eclipse Vans (profits and production quantity). Besides, the study will expose the forecast values of both quantity and profit. The study used various statistical tools to exhibit both the descriptive and predictive analysis, such as the measures of dispersion and central tendency, visual tools (pie and line graphs) and simple regression model. As evident, the 2018 recorded higher quantity and profit compared to 2017. The increase in profit may be attributed to option pack offer adopted by the management, thus it is recommendable for the management to develop adopt other offer, which may increase the profits.

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Executive Summary
The following study seeks to exhibit the descriptive statistics of Eclipse Vans (profits and
production quantity). Besides, the study will expose the forecast values of both quantity and
profit. The study used various statistical tools to exhibit both the descriptive and predictive
analysis, such as the measures of dispersion and central tendency, visual tools (pie and line
graphs) and simple regression model. As evident, the 2018 recorded higher quantity and profit
compared to 2017. The increase in profit may be attributed to option pack offer adopted by the
management, thus it is recommendable for the management to develop adopt other offer, which
may increase the profits.

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Table of Contents
Executive Summary.............................................................................................................1
Introduction..........................................................................................................................3
Eclipse Vans....................................................................................................................3
Methodology........................................................................................................................4
Data Analysis.......................................................................................................................4
Descriptive Statistics.......................................................................................................4
Quantity.......................................................................................................................4
Profits...........................................................................................................................6
Prediction.........................................................................................................................8
Regression Analysis.....................................................................................................8
Profit prediction...........................................................................................................9
Conclusion...........................................................................................................................9
Recommendation...............................................................................................................10
References..........................................................................................................................11

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Introduction
There is no doubt the primal purpose of a business is to generate income and make profit.
Moreover, its is the responsibility of any manufacturer or producer to meet the needs of different
consumers. As a result, manufacturers tend to produce various products to meet the customers’
expectations. Consequently, it is essential to evaluate the sustainability of a company to ensure
that in not only maintains but also improves its production level. Thus, it recommendable for the
business to forecast the demand, sales, supply, quantity, produced, revenues, and profits
associated with the products produced. Therefore, the following study seeks to exhibit the
descriptive statistics of Eclipse Vans (profits and production quantity). Besides, the study will
expose the forecast values of both quantity and profit.
Eclipse Vans
Eclipse Vans engages in the production, sales, and distribution of recreational vehicles,
which include motorhomes, camper trailers, Pop top, and Caravan. The company is managed by
both Abdul and Joeline, whereby Abdul is responsible for manufacturing process whereas
Joeline controls the staffing, accounts, reception, and customer services. Notably, to increase the
sales the management has incorporated advertisements in several magazines, which include
Camping, and 4WD; moreover, Joeline seeks to offer an options pack to customers, which could
be purchased at special discounted.

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Methodology
The study used various statistical tools to exhibit both the descriptive and predictive
analysis. For instance, both the measures of dispersion and central tendency were used to show
the descriptive statistics for both the quantity and profits (Manikandan, 2011). Besides, the visual
tools, such as pie and line graphs were used to exhibit the frequencies and trend. On the other
hand, predictive analysis utilized a simple regression model to exhibit the relationship between
the dependent and independent variables.
Data Analysis
Descriptive Statistics
Quantity
The following table exhibits the quantity of vans sold in 2017 and 2018.
Vehicle category 2017 2018
Cravan 128 170
Camper trailer 81 78
Pop top 49 91
Motorhome 2 2
The pie chart below shows the proportion of vans sold in 2017 and 2018
1
0 20 40 60 80 100 120 140
128
81
49
2
Number of vans sold in 2017
Motorhome
Pop top
Camper trailer
Cravan

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Cravan
Camper trailer
Pop top
Motorhome
0 20 40 60 80 100 120 140 160 180
170
78
91
2
Number of vans sold in 2018
Frequency
January
February
March
April
May
June
July
August
September
October
November
December
0
10
20
30
40
50
60
Vans Solds in 2017 and 2018
2017 2018
The trend graph above shows the number of vans sold across the two years, whereby
November recorded the highest volume whereas both July and August recorded the lowest
volume of vans sold in both 2017 and 2018. Moreover, it is evident that the 2018 recorded a
higher quantity than 2017, which may be attributed to advertisements and option pack offer to
the customers.
Descriptive
Statistics
2017 2018
Mean 21.58333333 28.5
Standard Error 3.283241039 4.305564
Median 23.5 32
Mode 30 32
Standard Deviation 11.37348058 14.91491

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Sample Variance 129.3560606 222.4545
Kurtosis -0.840475844 -0.68325
Skewness -0.510407244 -0.27461
Range 35 48
Minimum 2 4
Maximum 37 52
Sum 259 342
Count 12 12
As evident, 2018 recorded a higher mean of 28.5 (29) whereas 2017 had a mean of 21.58
(22). Besides, the total number of vans sold in 2017 were 259 whereas in 2018 were 342.
Profits
The following tables exhibit the profit generated by the type of vehicle and model for
both 2017 and 2018. Besides, it is evident that Camper trailer models contributed more to the
profit compared to other models.
Row Labels 2017 2018
Camper trailer 289430 276166
Escape 36 72910 90564
Escape 36R 109650 121808
Escape 42 60945 31434
Escape 42R 45925 32360
Caravan 1085315 1407096
Adventurer 50 28640 47179
Adventurer 50R 276500 366308
Adventurer 55 333535 410187
Adventurer 65 446640 583422
Motorhome 31200 31200
Tourer 85 31200 31200
Pop top 234960 421460
Safari 40 48540 98635
Safari 40R 55620 144995
Safari 45 23800 27160
Safari 45R 107000 150670
Grand Total 1640905 2135922

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The descriptive statistics below exhibit that 2018 recorded significantly higher mean and
total profit compared to 2018.
Descriptive Statistics 2017 2018
Mean 136742.0833 177993.5
Standard Error 21028.98689 28455.02579
Median 144817.5 197100
Standard Deviation 72846.54744 98571.10079
Sample Variance 5306619473 9716261911
Kurtosis -0.7510201 -0.596714413
Skewness -0.434004491 0.004931832
Range 230025 322289
Minimum 13485 26642
Maximum 243510 348931
Sum 1640905 2135922
Count 12 12
Similar to quantity line graph below shows trend of profits across the two years whereby
November recorded a higher profit whereas August had the least profit.
January
February
March
April
May
June
July
August
September
October
November
December
$-
$50,000.00
$100,000.00
$150,000.00
$200,000.00
$250,000.00
$300,000.00
$350,000.00
$400,000.00
Chart Title
2017 2018

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Prediction
Regression Analysis
Regression exhibits the association between explanatory and response variable (Beers,
2019)
Null Hypothesis: There is no relationship between months of the year and profits
generated
Alternative Hypothesis: There is a relationship between months of the year and profits
generated
Regression Statistics
Multiple R 0.289613522
R Square 0.083875992
Adjusted R Square 0.042233992
Standard Error 85639.67191
Observations 24
The R square above 0.0839 (8%) shows that the variation in the profits generated can be
explained by the months of the year at the rate of 8%.
ANOVA
df SS MS F Significance F
Regression 1 14772570634 14772570634 2.0142 0.169845746
Residual 22 1.61351E+11 7334153405
Total 23 1.76124E+11
At 5% significance level
The p-value (0.1698) is greater than the significance value (0.05) thus the model is not
adequate in explaining the variation in profitability.
Coefficients
Intercept 112566.6449
Months 3584.091739
Profit = 112566.65 + 3584.092Months

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Profit and Quantity prediction
Using the linear regression function the following graph exhibits the profits for the next
two years (2019 and 2020) whereby it is evident that by maintaining the current management
strategies the profits will tend to increase for the next two years. Moreover, it is evident that the
current management strategies will increase the quantity of the cars sold over the next two years.
Quantity = 18.634 + 0.5126Months
Profit = 112566.65 + 3584.092Months
The models above exhibit that the mean profit generated by the company will be
112566.65 whereas the mean quantity of cars sold is 18.63 (19); However, as time increases
(one-month increase) will result to the increase in profits by 3584.092 whereas the quantity will
increase by 0.5126. Therefore, the following graph exhibits the increase in both profit and
quantity. Notably, profit uses the primary y-axis (left) for reference whereas quantity uses the
secondary y-axis (right).
Jan-19
Mar-19
May-19
Jul-19
Sep-19
Nov-19
Jan-20
Mar-20
May-20
Jul-20
Sep-20
Nov-20
0
50000
100000
150000
200000
250000
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Profits prediction 2019 to 2020
Profits prediction Quantity Prediction

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Conclusion
As evident, the 2018 recorded higher quantity and profit compared to 2017. However, the
model is not adequate is explaining the variation in profit thus it is not sufficient in predicting the
profits. Therefore, other than months there are various factors such as type of van that aid in
predicting profitability.
Recommendation
Since Camper trailer models contributed more to the profit compared to other models it is
recommendable for company to produce more vans of this model. Besides, it the increase in
profit may be attributed to option pack offer adopted by the management, thus it is
recommendable for the management to develop and adopt other offer, which may increase the
profits.
Notably, a single van from the Motorhome model (Tourer 85) tends to generate the
highest profit of 15600 thus by increasing the number of sales of this model will result in the
increase in profits generated. Therefore, it is recommendable for the management to develop
strategies such as discount or after sales services to promote the sales of this product thus
improve the profits generated.
As evident, the Caravan model tends to be on higher demand in both 2017 and 2018 thus
due to its high demand the company can increase it cost by small percentage, which may not
adversely affect the level of demand rather increase the profits generated.

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References
Beers, B. (2019, May 23). Regression Definition . Retrieved from Investopedia Website:
https://www.investopedia.com/terms/r/regression.asp
Manikandan, S. (2011). Measures of central tendency: The mean. Journal of Pharmacol and
Pharmacotherapeutics, 2(2), 140-142. doi:10.4103/0976-500X.81920