Numeracy and Data Analysis Report: Wind Speed Statistical Analysis

This report provides a comprehensive analysis of wind speed data using various statistical methods and numeracy techniques. It includes calculations for mean, median, mode, range, and standard deviation, offering a detailed overview of wind speed distribution. Furthermore, the report utilizes linear forecasting to compute the values of 'm' and 'c,' which are essential for predicting future wind speeds, specifically for days 11 and 12. The analysis highlights the importance of statistical tools in forecasting and decision-making. Desklib provides access to a wide range of study resources, including past papers and solved assignments, to support students in their academic endeavors.

Numeracy and Data
Analysis

Contents
INTRODUCTION...........................................................................................................................3
TASK...............................................................................................................................................3
Mean............................................................................................................................................3
Median.........................................................................................................................................4
Mode............................................................................................................................................4
Range...........................................................................................................................................4
Standard Deviation......................................................................................................................5
Compute the value of m and c by the help of linear forecasting.................................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................8

INTRODUCTION
Statistical methods and techniques may be defined as an essential and crucial tool that would
help in scientific research Van der Linden W.J, 2017). It facilitates in designing the experiments
and analysing those figures along with interpretation. It enables the manager to take effective and
correct decisions that would help the firm in attaining its objectives. This project report will
cover the speed of wind in a country in terms of data analysis and numeracy. Further, it will
cover the tabular form chart in order to calculate mean, mode, median, range and standard
deviation. In addition to that, it will cover the linear forecasting so that it would compute the
value of “m” and “c” which helps in calculating Day 11 and Day 12 speed of wind. This is
considered as a base that would help in future forecasting.
TASK
Day 1 2 3 4 5 6 7 8 9 10 Total
Wind
speed
10 22 12 24 12 10 5 9 10 14 128
Calculation of data analysis
Mean
It refers to the average of set values. Mean can be computed in various ways. Following is the
step of computation of mean.
 Collect the given data.
 Sum up of all the values
 Number of total values
 Divide step two by step three.
Mean of speed of wind – Sum of given values/Total number of data set
=128 / 10
Mean = 12.8

Median
It may be defined as the midpoint of given data set. In simple words, it is a sorted either in
ascending or descending order in order to find the middle value of the given data set (George and
Mallery, 2018). Following is the calculation of Median
 Collect all the value data.
 Arrange the value in ascending or descending serial.
 Find out the data whether it is odd or even.
 Apply the formula (n+1)/2 if the n is odd.
 Apply the formula if n is even, N/2.
Median of speed of wind
10, 22, 12, 24, 12, 10, 5, 9, 10, 14
5, 9, 10, 10, 10, 12, 12, 14, 22, 24
Median = 10/2
Median = 5th term
Median= 10
Mode
It is the value that is highly repetitive in a given data set (Sun, Ouyang and Yue, 2017).
The given data may have one or more than one mode. Following are the steps to calculate
mode.
 Arrange the terms in ascending or descending order.
 Analyse the data that is repeated frequently.
 Select the number that is highly repeated.
5, 9, 10, 10, 10, 12, 12, 14, 22, 24
Mode of Wind Speed = 10
Range
It is the simplest term and can be obtained by subtracting the lowest value from the highest.
Following is the step to compute range.
 Sort the data.
 Select the highest and lowest value.
 Subtract the highest value from lowest.

 The value of range is computed in step 3.
Range = Highest value – Lowest Value
= 24 – 5
Range = 19
Standard Deviation
It may be referred as the value that is determined the total number of data that is spread
in context to mean. Following are the steps of standard deviation.
 Select one of the mean value.
 Compute all the data by deviation from mean.
 Do the sum of all squares.
 Divide by the total number of data.
 Square root of the above step figures.
 Standard Deviation= √∑ (xi – μ) 2 / N
Compute the value of m and c by the help of linear forecasting
Linear Forecasting Model – It may be referred as the technique of future data based on previous
data. It involves the detailed analysis of previous data and trends in order to predict the future. It
is also known as Statistical analysis. A well-defined forecast is unbiased which includes the
previous trends and based on that it forecasts the future events and demand (Saber and Alam,
2017). Following are the steps of linear forecasting.
 Analyse the problem that is arising.
 Collect the information needed through surveys.
 Analyse the information and truthfulness of its source.
 Opt the model which is suitable to conduct series of linear forecasting.
 Observe the information carefully.
y = mx + C
where, 'y' is Dependent Factor,
'mx' is Independent factor and
'c' is constant Factor
Series for the calculation of “m”

 Count the total number and multiply both the term along with count.
 Sum the total of “x” and “y” separately.
 Subtract step two from one.
 Compute the square of x and multiply with the count of total.
 Compute the square of “x”
 Subtract step 5 from 4.
 Divide the figure of step 6 by step 6.
Computation of “c”.
 Add the total value of y variable.
 Calculate the value of m and calculate it with the value of x variable.
 Subtract step 2 from 1.
 Calculate the total of x variable.
 Divide the result of step 4 with N.
CONCLUSION
From the above project report, it was concluded that statistical tools and techniques plays an
important role in forecasting the future values by taking base of previous data. It enables the
manger in taking effective decisions in order to attain the company’s objectives. There are
various sets of series that a manager has to perform so that it can obtain the accurate results. In
case of any error while entering data it may not give the accurate data. The above project report

had calculated mean, mode, median, range and standard deviation of speed of wind in a
particular country.

REFERENCES
Books and Journals
Van der Linden, W.J. ed., 2017. Handbook of Item Response Theory: Volume 2: Statistical
Tools. CRC Press.
George, D. and Mallery, P., 2018. Descriptive statistics. In IBM SPSS Statistics 25 Step by
Step (pp. 126-134). Routledge.
Saber, A.Y. and Alam, A.R., 2017, November. Short term load forecasting using multiple linear
regression for big data. In 2017 IEEE symposium series on computational intelligence
(SSCI) (pp. 1-6). IEEE.
Sun, X., Ouyang, Z. and Yue, D., 2017, November. Short-term load forecasting based on
multivariate linear regression. In 2017 IEEE Conference on Energy Internet and Energy System
Integration (EI2) (pp. 1-5). IEEE.