Wind Speed Data Analysis and Linear Forecasting in Numeracy Course

This report provides a comprehensive analysis of wind speed data, utilizing various statistical measures such as mean, median, mode, range, and standard deviation. It includes a detailed computation of these measures based on a given dataset. Furthermore, the report applies the linear forecasting theory to predict future wind speeds, demonstrating the calculation of 'm' and 'c' values in the forecasting model. The analysis concludes with predictions for wind speed on days 12 and 14, offering insights into the application of statistical and mathematical tools for data analysis and forecasting. Desklib is a valuable resource for students seeking similar solved assignments and past papers to enhance their understanding.

Project Brief

Contents
INTRODUCTION...........................................................................................................................2
MAIN BODY..................................................................................................................................2
1. Compute the data of the country in a table (Hudson and Willoughby, 2021).........................2
2. Show wind speed of the country in Chart Format...................................................................2
4. Using Linear Predicting model do regression investigates and discover the worth of c and
m..................................................................................................................................................5
CONCLUSION................................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
The following report describe the mean, median, mode, standard deviation, range, Lineal
Forecasting Theory on the basis of country wind speed data. The mean is generally helpful for
calculating the average, the medium is most commonly useful for determining the mid-point and
the mode is useful to analyse the most repeatable value. In this following table all the statistical
and mathematical tools are measures used to represent a midline of a set of data.
MAIN BODY
TASK
1. Compute the data of the country in a table (Hudson and Willoughby, 2021).
Day
Wind
Speed
1 22
2 14
3 15
4 14
5 23
6 22
7 14
8 15
9 14
10 23
Total 176
2. Show wind speed of the country in Chart Format

Chart: Chart shows different temperature of the previous 10 days.
Mean = Mean is an integral concept of statistics and mathematics. It refers to the average value
for a given set of numbers in the series. It is derived from two or more numbers of data set. Mean
signify the equal division of values for a given statistics set. The formula of mean is calculated
by dividing the sum of all the set of data points by the Number of data points (Westwood., 2021).
Steps which is used to calculate the Mean:
Step 1: Collect all set of data

Step 2: Sum of all the data points
Step 3: Add all the number of data points
Step 4: Divide the Total numbers of data points from sum of all data points
Mean = Sum of all data points / Number of data points
Mean = 176 / 10
Mean = 17.6
Median = Median value is derived after sorting a data as an ascending or a descending order and
then the result is calculated (Cohrssen and Niklas., 2019).
Steps should be taken for calculating the mean:
Step 1: First of all, to arrange the data in ascending or descending order.
Step 2: Add total numbers of data points.
Step 3: Analyse and observe the value of medium in terms of odd and even
Step 4: If the Medium value is odd then it is calculated as (N+1)/2.
Step 5: The medium value id even then it is calculated as a simple method.
Following are the formula of calculating the Medium value:
Median Value (if even) = N / 2
Median value (if odd) = (N+1) / 2
Calculation of wind speed median:
22, 14, 15, 14, 23, 22 ,14, 15, 14, 23
14, 14, 14, 14, 15, 15, 22, 22, 23, 23
Median = N / 2
=15 / 2
=7.5th position
Median = (15 + 15) / 2
=30 / 2
=15
Mode = The number which have higher number of probability is equal to mode.
Steps of calculating the value of mode:
Step1: Sort the data in terms of ascending and descending order.
Step2: Observe all the value in a data points.
Step3: Count how many of each number.

Step4: Pick the number which have higher number of probability.
22, 14, 15, 14, 23, 22 ,14, 15, 14, 23
Mode = 14
Range = The range is the difference between the largest value and smallest value. In other
words, it is calculated by subtracting the highest value from the lowest value (Roberts, Thier and
Beach., 2021).
Following steps to calculate the range are:
Step1: Arrange the data in a systematic manner
Step2: Analyse the highest and lowest value
Step3: Deduct the lowest value form highest value
Step4: In result, the value of range is derived.
Range = Highest value – Lowest Value
= 23 – 14
=9
Standard deviation = It shows that how much data is scattered is in relation to the value of
mean.
Here, Measure steps to calculate the standard deviation
Step 1: First of all, observe the value of mean.
Step 2: After that calculate each data point deviation from mean.
Step 3: Then find out the square.
Step 4: further divide by the total number of data set
Step 5: In the end, take the square root for calculating the standard deviation.
Standard Deviation= √∑ (xi – μ) 2 / N
=√162.4 / 10
= 4.029
4. Using Linear Predicting model do regression investigates and discover the worth of c and m.
Lineal Forecasting Theory: It is helpful for future forecasting and it is prepared on the basis of
past experience. Following are the formula to calculate the Lineal forecasting theory (Schreiber.,
2021.) :
There are following steps to calculate lineal Forecasting Theory:
Step1: Analyse the problem arising.
Step2: Gather the information

Step3: Perform a beginning analysis
Step4: Choose the model for forecasting activity.
Step5: Then analysis the data
Step6: Check the performance of model
y = mx + C
where, 'y' is stands for Dependent Factor,
'mx' is stands for Independent factor and
'c' stands for constant Factor
Following are the ways to calculate the value of 'm':
1. Multiply the value of both the factors.
2. Add the total value calculated
3. Each factor should be added separately.
4. Multiply the value of both the variables.
5. Than calculate the value.
m = (10*972 – 55*176) / (10*385 – 3025)
m = (9720 – 9680) / (3850 – 3025)
m= 40 / 825
m = 0.048
Steps for calculating worth of 'c'
Step1: First of all, Calculate the sum of 'y' factors.
Step2: Calculate the value of 'y' variable.
Step3: divide the sum with value 'N'.
Step4: After the above calculation the Worth of 'c' is calculated.
c = (176 – (0.048*55)) / 10
c = (176 – 2.64) / 10

c = 173.36 / 10
c = 17.336
Wind speed on Day 12: -
m = 0.048, c = 17.336, x = 12
y = mx + c
y = 0.048*12 + 17.336
y = 0.576 + 17.336
y = 17.912
Wind Speed on Day 14: -
m = 0.048, c = 17.336, x = 12
y = mx + c
y = 0.048*14 + 17.336
y = 0.672 + 17.336
y = 18.008
CONCLUSION
In the above represent the 10days wind speed data of the country and also helpful for the future
forecasting. They helpful in calculating wind speed of the country with the help of mean,
median, mode, range, standard deviation and lineal forecasting theory. Lineal forecasting theory
is helpful in determining the day 12 and day 14 wind speed of the country.

REFERENCES
Books and Journals
Hudson, K.N. and Willoughby, M.T., 2021. Evaluating the Factor Structure and Criterion
Validity of the Canadian Little DCDQ: Associations Between Motor Competence,
Executive Functions, Early Numeracy Skills, and ADHD in Early Childhood. Assessment,
p.10731911211003967.
Westwood, P.S., 2021. Teaching for Numeracy Across the Age Range: An Introduction.
Springer Singapore.
Cohrssen, C. and Niklas, F., 2019. Using mathematics games in preschool settings to support the
development of children’s numeracy skills. International Journal of Early Years
Education. 27(3). pp.322-339.
Roberts, P., Thier, M. and Beach, P., 2021. Erasing rurality: On the need to disaggregate
statistical data. In Ruraling Education Research (pp. 107-127). Springer, Singapore.
Schreiber, J.B., 2021. Be Careful! That is Probably Bullshit! Review of Calling Bullshit: The Art
of Skepticism in a Data-Driven World by Carl T. Bergstrom and Jevin D.
West. Numeracy, 14(2), p.10.