Data Analysis Report: Statistical Methods and Forecasting

Desklib provides solved assignments and past papers to help students succeed.

Table of Contents
Main Body..................................................................................................................................2
References..................................................................................................................................7
List of Figures
Figure 1: Tabular Data...............................................................................................................2
Figure 2: Line Chart...................................................................................................................2
Figure 3: 3D-Column Chart.......................................................................................................3
Figure 4: Calculated results........................................................................................................5
Figure 5: Forecasted values........................................................................................................6

Main Body
1.
Figure 1: Tabular Data
The above-shown data is represented in the form of the tables and it contains the data related
to the temperature of ten consecutive days. Various information regarding the Weather,
Wind, Visibility, Humidity, and Barometer is also shown in the form of the table.
2.
The above data is then represented in the form of the charts. The two out of many charts are
being used here to display the data in visual form. The charts being used here are:
Line Chart
Line Chart is the chart used here in order to represent the data of the ten consecutive days.
Here, the temperature and the dates are compared and shown in the form of the Line Chart.
The X-axis of the Line chart shows the dates whereas the Y-axis of the Line chart shows the
changes in the temperature.

Figure 2: Line Chart
Column Chart
Column Chart is the next chart used here to represent the data of the temperature and other
attributes for the ten consecutive days (Ioannou, I. and Angeli, C., 2015). Here, the wind is
compared on the basis of different dates and then the whole information is shown in the form
of the 3D- Column Chart. The X-axis of the Column chart shows the dates whereas the Y-
axis of the Line chart shows the changes in the wind.

Figure 3: 3D-Column Chart
3.
i). Mean is being calculated as:
Firstly, the entire values are sum-up and then the sum is being divided with the number of
items. Here, the mean of the temperature, wind, barometer, and visibility is being calculated.
Step 1- Each of the values is being sum-up.
Step 2- Then, the sum of the values is divided with the number of items present in the data.
Formula used for calculating the mean is:
Mean=Sum of items/Number of Items
Temperature = 3.3
Wind = 7.9
Humidity = 0.916
Barometer = 1023.4
Visibility = 11
ii). Median is being calculated as:
Secondly, calculating the median of the data is to be done. Here, firstly the number of items
are added with 1 and then gets divided by 2. By using the given formula below, the median is
calculated.

Step 1- Firstly, the data is arranged in the ascending order.
Step 2- Secondly, the number of items is sum-up with 1.
Step 3- Thirdly, it is divided by 2 and the median value is calculated.
Step 4- Then, if the middle value is single then it is considered as the Median else if two
values are taken then sum of them gets divided by 2.
Formula used for calculating the median is:
Median= (number of items + 1)/2
Temperature = 3.5
Wind = 5.5
Humidity = 0.93
Barometer = 1023.5
Visibility = 9
iii). Mode is being calculated as:
Thirdly, the mode of the data is to be calculated. The calculation of the mode of the data
doesn’t require any formula. The mode is calculated as the item that is occurred a maximum
number of items.
Mode is:
Temperature = 4
Wind = 5
Humidity = 0.93
Barometer = 1014
iv). The range is being calculated as:
The fourth part contains the calculation of the Range. The range is calculated as the
difference between the low range and the high range. Low range is calculated with the use of
the Min function and High Range is calculated by using the Max function.
The range is calculated as:

Range = High Range-Low Range
Temperature = 4
Wind = 17
Humidity = 0.24
Barometer = 37
Visibility- 8
v). Standard Deviation is being calculated as:
Last part contains the calculation of the Standard deviation and the formula being used
here is the:
Step 1- Mean is being calculated in the first step.
Step 2- Then, each of the items is then subtracted from the mean value and square value of
the result is taken.
Step 3- Sum of the items is done (Krishnacharya et al., 2016).
Step 4- Final value is then calculated.
SD is:
Temperature = 1.63
Wind = 5.89
Humidity = 0.8
Barometer = 12.79
Visibility- 4.35

Figure 4: Calculated results
4.
i). The value of m is to be calculated as:
Steps are-
Step 1- Firstly, the number of items are counted.
Step 2- Each of the temperatures is multiplied with the respective day.
Step 3- Each of the value of the temperature is squared and then added up.
Step 4- All these values are then inserted in the formula to calculate the value of m.
M= N ∑XY-∑X∑Y/N∑X2 – (∑X)2
Here, N = no. of items, X- Temperature, Y-Days
ii). The value of c can directly be calculated by using the simple formula as:
c = ∑Y-M∑X/N
iii). Forecast for the day 15th and 23rd can directly be calculated using the values of m
and c that are calculated by the use of the above-mentioned formulae.
For the 15th day, the value calculated is the – 1.975

For the 23rd day, the value calculated is the – 0.86
These both values are calculated by putting the formula above, and Y is the variable
that has to be calculated.
Figure 5: Forecasted values

References
 Ioannou, I. and Angeli, C., 2015. Technological pedagogical content knowledge as a
framework for integrating educational technology in the teaching of computer science.
In Technological pedagogical content knowledge (pp. 225-237). Springer, Boston, MA.
 Krishnacharya, P.S., Singal, A.K., Naaz, A.S., Arra, R.R., Angadi, P.A. and
Chandramouli, A., 2016. Validity of Novel Microsoft Excel Software for Calculating
Surgically Induced Astigmatism. Ophthalmology Research: An International Journal,
pp.1-9.