PRACTICAL
Consider a class of 16 students taking statistics course, and their names, marks, and major subjects are given in the following table:
| S. No. | Name | Marks | Major |
| 1 | A | 92 | Maths |
| 2 | B | 97 | Maths |
| 3 | C | 68 | Statistics |
| 4 | D | 62 | Maths |
| 5 | E | 97 | Statistics |
| 6 | F | 68 | Maths |
| 7 | G | 76 | Statistics |
| 8 | H | 75 | Statistics |
| 9 | I | 51 | Maths |
| 10 | J | 94 | Maths |
| 11 | K | 70 | Maths |
| 12 | L | 89 | Statistics |
| 13 | M | 62 | Maths |
| 14 | N | 63 | Maths |
| 15 | O | 48 | Maths |
| 16 | P | 97 | Maths |
(i) Compute the following parameters:-
(a) Population Mean
(b) Population Variance
(c) Population Standard Deviation
(d) Population Mean Square Error
(ii) (a) Select an SRSWOR sample of 4 units using a random number method.
(b) Compute the population proportion of students with a major in statistics.
(c) Compute the variance of the estimator of population proportion.
(d) Estimate the variance of the estimator of population proportion.
Theory-
- Theory of I part
Population mean is given by-
Sample mean is given by-
Population variance is given by-
Population standard deviation is given by-
Population mean square error is given by-
- Theory of 2nd part
Population proportion is given by-
Variance of population proportion is given by-
Estimated variance of population proportion is given by-
Where,
NA is the number of units in the population having A characteristics and N is the total population size.
N = population size
n = sample size
QY = 1-PY
is sample proportion.
Where nA is the unit in the sample having characteristics A.
R Code-
#command to remove previous objects
rm(list=ls())
#loading and viewing data set
Student_Data = read.csv("class work 08b.csv")
View(Student_Data)
#checking the class of the dataset
data.class(Student_Data)
#loading dataset on environment
attach(Student_Data)
#population mean marks, varience,sd and population mean square error
N= length(Marks)
Mean_marks = mean(Marks)
Marks_varience = var(Marks)
Marks_sd = sd(Marks)
Marks_S = (N/(N-1))*Marks_varience
Parameter=c("Population Mean","Population Varience","Standard Deviation","Popul. Mean Sq. Error")
Calculated_Values=c(Mean_marks,Marks_varience,Marks_sd,Marks_S)
#selecting sample of size 4 with SRSWOR
n=4 #given sample size
Random_sample = sample(N,n,replace = F)
Random_sample
Logic=S..No.==Random_sample[1]|S..No.==Random_sample[2]|S..No.==Random_sample[3]|S..No.==Random_sample[4]
Sample_Data=subset(Student_Data,Logic)
#students having major as Statistics in population
Student_Data_Ststs=subset(Student_Data,Major=="Statistics")
#calculating population prop. of students having statistics as major
N_stats = length(Student_Data_Ststs$Marks)
P_Stats = N_stats/N
#calculating varience of estimator of population proportion
Q_stats = 1-P_Stats
Var_P_cap_stats = ((N-n)/(n*(N-1))) * P_Stats*Q_stats
#students having major as Statistics in sample
Sample_Data_stats = subset(Sample_Data,Sample_Data$Major=="Statistics")
#estimating varience of estimater of population prop. from obtained sample
r_stats = length(Sample_Data_stats$Marks)
p_stats = r_stats/n
q_stats = 1 - p_stats
Var_cap_P_cap_stats = ((N-n)/(N*(n-1))) * p_stats*q_stats
#Final Solutions
#Given Population Data
cat("Given population data:-\n")
data.frame(Student_Data)
#(i.)
cat("calculated Population mean, varience, s.d., and population mean square error are as follows:-\n")
data.frame(Parameter,Calculated_Values)
#(ii.) a.
cat("Selected sample data by SRSWOR is :-\n")
data.frame(Sample_Data)
#(ii.) b.
cat("Students having Statistics as major subject in the population is as follows:- \n")
data.frame(Student_Data_Ststs)
cat("population proportion of students having Statistics as major is :",P_Stats,"\n")
#(ii.) c.
cat("Calculated varience of the estimator of the population proportion is :",Var_P_cap_stats,"\n")
#(ii.) d.
cat("Number of students having Statistics as major in the obtained sample is as follows :-\n")
data.frame(Sample_Data_stats)
cat("Estimated varience of estimator of population proportion from sample is :",Var_cap_P_cap_stats,"\n")
Output From R Console (Final Solution Part)
> #Final Solutions
>
>
> #Given Population Data
> cat("Given population data:-\n")
Given population data:-
> data.frame(Student_Data)
S..No. Name Marks Major
1 1 A 92 Maths
2 2 B 97 Maths
3 3 C 68 Statistics
4 4 D 62 Maths
5 5 E 97 Statistics
6 6 F 68 Maths
7 7 G 76 Statistics
8 8 H 75 Statistics
9 9 I 51 Maths
10 10 J 94 Maths
11 11 K 70 Maths
12 12 L 89 Statistics
13 13 M 62 Maths
14 14 N 63 Maths
15 15 O 48 Maths
16 16 P 97 Maths
>
>
> #(i.)
> cat("calculated Population mean, varience, s.d., and population mean square error are as follows:-\n")
calculated Population mean, varience, s.d., and population mean square error are as follows:-
> data.frame(Parameter,Calculated_Values)
Parameter Calculated_Values
1 Population Mean 75.56250
2 Population Varience 280.26250
3 Standard Deviation 16.74104
4 Popul. Mean Sq. Error 298.94667
>
>
> #(ii.) a.
> cat("Selected sample data by SRSWOR is :-\n")
Selected sample data by SRSWOR is :-
> data.frame(Sample_Data)
S..No. Name Marks Major
1 1 A 92 Maths
7 7 G 76 Statistics
11 11 K 70 Maths
12 12 L 89 Statistics
>
>
> #(ii.) b.
> cat("Students having Statistics as major subject in the population is as follows:- \n")
Students having Statistics as major subject in the population is as follows:-
> data.frame(Student_Data_Ststs)
S..No. Name Marks Major
3 3 C 68 Statistics
5 5 E 97 Statistics
7 7 G 76 Statistics
8 8 H 75 Statistics
12 12 L 89 Statistics
> cat("population proportion of students having Statistics as major is :",P_Stats,"\n")
population proportion of students having Statistics as major is : 0.3125
>
>
> #(ii.) c.
> cat("Calculated varience of the estimator of the population proportion is :",Var_P_cap_stats,"\n")
Calculated varience of the estimator of the population proportion is : 0.04296875
>
>
> #(ii.) d.
> cat("Number of students having Statistics as major in the obtained sample is as follows :-\n")
Number of students having Statistics as major in the obtained sample is as follows :-
> data.frame(Sample_Data_stats)
S..No. Name Marks Major
7 7 G 76 Statistics
12 12 L 89 Statistics
> cat("Estimated varience of estimator of population proportion from sample is :",Var_cap_P_cap_stats,"\n")
Estimated varience of estimator of population proportion from sample is : 0.0625
Conclusion-
- Population mean, variance, standard deviation and population mean square error are 75.56250, 280.26250, 16.74104 and 298.94667 respectively.
- Selected random sample is-
S..No. Name Marks Major
1 1 A 92 Maths
7 7 G 76 Statistics
11 11 K 70 Maths
12 12 L 89 Statistics
- Students having major subject as statistics are-
S..No. Name Marks Major
3 3 C 68 Statistics
5 5 E 97 Statistics
7 7 G 76 Statistics
8 8 H 75 Statistics
12 12 L 89 Statistics
- Calculated varience of the estimator of the population proportion is : 0.04296875.
- Estimated varience of estimator of population proportion from sample is : 0.0625.