346.INDIAN STATES SOCIO-ECONOMIC DATA ANALYSIS USING DATA STEP | PROC SQL | PROC MEANS | PROC CORR | PROC UNIVARIATE | MACROS | DATE FUNCTIONS

INDIAN STATES SOCIO-ECONOMIC DATA ANALYSIS USING DATA STEP | PROC SQL | PROC MEANS |  PROC CORR | PROC UNIVARIATE | MACROS | DATE FUNCTIONS

 options nocenter;

1.INDIAN STATES DATASET CREATION WITH DATE FORMATS

data indian_states;

    length State $20;

    format Data_Date date9.;

    input State $ Literacy_Rate GDP Population Industrial_Growth Employment_Rate 

          Data_Date :date9.;

    datalines;

Andhra_Pradesh 67.4 13.5 53 6.2 59.1 01JAN2023

Telangana 72.8 14.2 39 7.5 61.4 01JAN2023

Tamil_Nadu 80.1 23.1 76 8.1 64.8 01JAN2023

Karnataka 75.6 21.9 68 7.9 63.2 01JAN2023

Kerala 94.0 9.8 35 5.1 60.9 01JAN2023

Maharashtra 82.3 38.5 125 6.9 62.7 01JAN2023

Gujarat 78.0 25.6 70 8.4 65.3 01JAN2023

Rajasthan 66.1 12.7 81 5.8 58.4 01JAN2023

Uttar_Pradesh 69.7 17.1 235 4.9 56.2 01JAN2023

Madhya_Pradesh 70.6 11.4 86 5.3 57.1 01JAN2023

West_Bengal 76.3 14.9 99 6.1 60.2 01JAN2023

Punjab 75.8 7.6 30 5.7 61.0 01JAN2023

;

run;

proc print data=indian_states;

run;

OUTPUT:

Obs	State	Data_Date	Literacy_Rate	GDP	Population	Industrial_Growth	Employment_Rate
1	Andhra_Pradesh	01JAN2023	67.4	13.5	53	6.2	59.1
2	Telangana	01JAN2023	72.8	14.2	39	7.5	61.4
3	Tamil_Nadu	01JAN2023	80.1	23.1	76	8.1	64.8
4	Karnataka	01JAN2023	75.6	21.9	68	7.9	63.2
5	Kerala	01JAN2023	94.0	9.8	35	5.1	60.9
6	Maharashtra	01JAN2023	82.3	38.5	125	6.9	62.7
7	Gujarat	01JAN2023	78.0	25.6	70	8.4	65.3
8	Rajasthan	01JAN2023	66.1	12.7	81	5.8	58.4
9	Uttar_Pradesh	01JAN2023	69.7	17.1	235	4.9	56.2
10	Madhya_Pradesh	01JAN2023	70.6	11.4	86	5.3	57.1
11	West_Bengal	01JAN2023	76.3	14.9	99	6.1	60.2
12	Punjab	01JAN2023	75.8	7.6	30	5.7	61.0

2.DATE FUNCTIONS USING INTNX AND INTCK

data indian_states_dates;

    set indian_states;

    Next_Year = intnx('year', Data_Date, 1, 'same');

    Months_Since = intck('month', Data_Date, '01JAN2024'd);

    format Next_Year date9.;

run;

proc print data=indian_states_dates;

run;

OUTPUT:

Obs	State	Data_Date	Literacy_Rate	GDP	Population	Industrial_Growth	Employment_Rate	Next_Year	Months_Since
1	Andhra_Pradesh	01JAN2023	67.4	13.5	53	6.2	59.1	01JAN2024	12
2	Telangana	01JAN2023	72.8	14.2	39	7.5	61.4	01JAN2024	12
3	Tamil_Nadu	01JAN2023	80.1	23.1	76	8.1	64.8	01JAN2024	12
4	Karnataka	01JAN2023	75.6	21.9	68	7.9	63.2	01JAN2024	12
5	Kerala	01JAN2023	94.0	9.8	35	5.1	60.9	01JAN2024	12
6	Maharashtra	01JAN2023	82.3	38.5	125	6.9	62.7	01JAN2024	12
7	Gujarat	01JAN2023	78.0	25.6	70	8.4	65.3	01JAN2024	12
8	Rajasthan	01JAN2023	66.1	12.7	81	5.8	58.4	01JAN2024	12
9	Uttar_Pradesh	01JAN2023	69.7	17.1	235	4.9	56.2	01JAN2024	12
10	Madhya_Pradesh	01JAN2023	70.6	11.4	86	5.3	57.1	01JAN2024	12
11	West_Bengal	01JAN2023	76.3	14.9	99	6.1	60.2	01JAN2024	12
12	Punjab	01JAN2023	75.8	7.6	30	5.7	61.0	01JAN2024	12

3.PROC SQL FOR DERIVED METRICS

proc sql;

    create table state_metrics as

    select State,Literacy_Rate,GDP,Population,Industrial_Growth,Employment_Rate,

           GDP/Population as GDP_Per_Capita format=8.2

    from indian_states;

quit;

proc print data=state_metrics;

run;

OUTPUT:

Obs	State	Literacy_Rate	GDP	Population	Industrial_Growth	Employment_Rate	GDP_Per_Capita
1	Andhra_Pradesh	67.4	13.5	53	6.2	59.1	0.25
2	Telangana	72.8	14.2	39	7.5	61.4	0.36
3	Tamil_Nadu	80.1	23.1	76	8.1	64.8	0.30
4	Karnataka	75.6	21.9	68	7.9	63.2	0.32
5	Kerala	94.0	9.8	35	5.1	60.9	0.28
6	Maharashtra	82.3	38.5	125	6.9	62.7	0.31
7	Gujarat	78.0	25.6	70	8.4	65.3	0.37
8	Rajasthan	66.1	12.7	81	5.8	58.4	0.16
9	Uttar_Pradesh	69.7	17.1	235	4.9	56.2	0.07
10	Madhya_Pradesh	70.6	11.4	86	5.3	57.1	0.13
11	West_Bengal	76.3	14.9	99	6.1	60.2	0.15
12	Punjab	75.8	7.6	30	5.7	61.0	0.25

4.PROC MEANS (DESCRIPTIVE STATISTICS)

proc means data=indian_states mean min max std;

    var Literacy_Rate GDP Population Industrial_Growth Employment_Rate;

run;

OUTPUT:

The MEANS Procedure

Variable	Mean	Minimum	Maximum	Std Dev
Literacy_Rate GDP Population Industrial_Growth Employment_Rate	75.7250000 17.5250000 83.0833333 6.4916667 60.8583333	66.1000000 7.6000000 30.0000000 4.9000000 56.2000000	94.0000000 38.5000000 235.0000000 8.4000000 65.3000000	7.5975026 8.5741816 55.2094497 1.2295294 2.8579899

5.PROC CORR (RELATIONSHIP ANALYSIS)

proc corr data=indian_states;

    var Literacy_Rate GDP Industrial_Growth Employment_Rate;

run;

OUTPUT:

The CORR Procedure

4 Variables:	Literacy_Rate GDP Industrial_Growth Employment_Rate

Simple Statistics
Variable	N	Mean	Std Dev	Sum	Minimum	Maximum
Literacy_Rate	12	75.72500	7.59750	908.70000	66.10000	94.00000
GDP	12	17.52500	8.57418	210.30000	7.60000	38.50000
Industrial_Growth	12	6.49167	1.22953	77.90000	4.90000	8.40000
Employment_Rate	12	60.85833	2.85799	730.30000	56.20000	65.30000

Pearson Correlation Coefficients, N = 12 Prob > |r| under H0: Rho=0
	Literacy_Rate	GDP	Industrial_Growth	Employment_Rate
Literacy_Rate	1.00000	0.22374 0.4845	0.09734 0.7634	0.51749 0.0849
GDP	0.22374 0.4845	1.00000	0.58529 0.0456	0.55222 0.0626
Industrial_Growth	0.09734 0.7634	0.58529 0.0456	1.00000	0.86941 0.0002
Employment_Rate	0.51749 0.0849	0.55222 0.0626	0.86941 0.0002	1.00000

6.PROC UNIVARIATE (DISTRIBUTION ANALYSIS)

proc univariate data=indian_states;

    var GDP Population;

    histogram GDP Population;

run;

OUTPUT:

The UNIVARIATE Procedure

Variable: GDP

Moments
N	12	Sum Weights	12
Mean	17.525	Sum Observations	210.3
Std Deviation	8.57418165	Variance	73.5165909
Skewness	1.40366643	Kurtosis	2.22885838
Uncorrected SS	4494.19	Corrected SS	808.6825
Coeff Variation	48.9254302	Std Error Mean	2.47515304

Basic Statistical Measures
Location		Variability
Mean	17.52500	Std Deviation	8.57418
Median	14.55000	Variance	73.51659
Mode	.	Range	30.90000
		Interquartile Range	10.45000

Tests for Location: Mu0=0
Test	Statistic		p Value
Student's t	t	7.08037	Pr > |t|	<.0001
Sign	M	6	Pr >= |M|	0.0005
Signed Rank	S	39	Pr >= |S|	0.0005

Quantiles (Definition 5)
Level	Quantile
100% Max	38.50
99%	38.50
95%	38.50
90%	25.60
75% Q3	22.50
50% Median	14.55
25% Q1	12.05
10%	9.80
5%	7.60
1%	7.60
0% Min	7.60

Extreme Observations
Lowest		Highest
Value	Obs	Value	Obs
7.6	12	17.1	9
9.8	5	21.9	4
11.4	10	23.1	3
12.7	8	25.6	7
13.5	1	38.5	6

The UNIVARIATE Procedure

The UNIVARIATE Procedure

Variable: Population

Moments
N	12	Sum Weights	12
Mean	83.0833333	Sum Observations	997
Std Deviation	55.2094497	Variance	3048.08333
Skewness	2.07706004	Kurtosis	5.35833297
Uncorrected SS	116363	Corrected SS	33528.9167
Coeff Variation	66.4506917	Std Error Mean	15.9375953

Basic Statistical Measures
Location		Variability
Mean	83.08333	Std Deviation	55.20945
Median	73.00000	Variance	3048
Mode	.	Range	205.00000
		Interquartile Range	46.50000

Tests for Location: Mu0=0
Test	Statistic		p Value
Student's t	t	5.213041	Pr > |t|	0.0003
Sign	M	6	Pr >= |M|	0.0005
Signed Rank	S	39	Pr >= |S|	0.0005

Quantiles (Definition 5)
Level	Quantile
100% Max	235.0
99%	235.0
95%	235.0
90%	125.0
75% Q3	92.5
50% Median	73.0
25% Q1	46.0
10%	35.0
5%	30.0
1%	30.0
0% Min	30.0

Extreme Observations
Lowest		Highest
Value	Obs	Value	Obs
30	12	81	8
35	5	86	10
39	2	99	11
53	1	125	6
68	4	235	9

The UNIVARIATE Procedure

7.MACRO FOR STATE-LEVEL CATEGORIZATION

%macro categorize_state;

data categorize_states;

    set indian_states;

    length Development_Level $15;

    if GDP >= 20 and Literacy_Rate >= 75 then Development_Level = "High";

    else if GDP >= 10 then Development_Level = "Medium";

    else Development_Level = "Low";

run;

proc print data=categorize_states;

run;

%mend;

%categorize_state;

OUTPUT:

Obs	State	Data_Date	Literacy_Rate	GDP	Population	Industrial_Growth	Employment_Rate	Development_Level
1	Andhra_Pradesh	01JAN2023	67.4	13.5	53	6.2	59.1	Medium
2	Telangana	01JAN2023	72.8	14.2	39	7.5	61.4	Medium
3	Tamil_Nadu	01JAN2023	80.1	23.1	76	8.1	64.8	High
4	Karnataka	01JAN2023	75.6	21.9	68	7.9	63.2	High
5	Kerala	01JAN2023	94.0	9.8	35	5.1	60.9	Low
6	Maharashtra	01JAN2023	82.3	38.5	125	6.9	62.7	High
7	Gujarat	01JAN2023	78.0	25.6	70	8.4	65.3	High
8	Rajasthan	01JAN2023	66.1	12.7	81	5.8	58.4	Medium
9	Uttar_Pradesh	01JAN2023	69.7	17.1	235	4.9	56.2	Medium
10	Madhya_Pradesh	01JAN2023	70.6	11.4	86	5.3	57.1	Medium
11	West_Bengal	01JAN2023	76.3	14.9	99	6.1	60.2	Medium
12	Punjab	01JAN2023	75.8	7.6	30	5.7	61.0	Low

8.ADDITIONAL SAS PROCEDURE

proc print data=categorize_states(obs=5);

    title "Indian States Development Classification";

run;

OUTPUT:

Indian States Development Classification

Obs	State	Data_Date	Literacy_Rate	GDP	Population	Industrial_Growth	Employment_Rate	Development_Level
1	Andhra_Pradesh	01JAN2023	67.4	13.5	53	6.2	59.1	Medium
2	Telangana	01JAN2023	72.8	14.2	39	7.5	61.4	Medium
3	Tamil_Nadu	01JAN2023	80.1	23.1	76	8.1	64.8	High
4	Karnataka	01JAN2023	75.6	21.9	68	7.9	63.2	High
5	Kerala	01JAN2023	94.0	9.8	35	5.1	60.9	Low

9.PROC CORR

proc corr data=indian_states;

    var Literacy_Rate GDP Population Employment_Rate;

    table Literacy_Rate*GDP;

run;

/* Note: In practice above there is an Invalid in this code Find it,Correct it and Use it /*

OUTPUT:

The CORR Procedure

1 With Variables:	GDP
4 Variables:	Literacy_Rate GDP Population Employment_Rate

Simple Statistics
Variable	N	Mean	Std Dev	Sum	Minimum	Maximum
GDP	12	17.52500	8.57418	210.30000	7.60000	38.50000
Literacy_Rate	12	75.72500	7.59750	908.70000	66.10000	94.00000
Population	12	83.08333	55.20945	997.00000	30.00000	235.00000
Employment_Rate	12	60.85833	2.85799	730.30000	56.20000	65.30000

Pearson Correlation Coefficients, N = 12 Prob > |r| under H0: Rho=0
	Literacy_Rate	GDP	Population	Employment_Rate
GDP	0.22374 0.4845	1.00000	0.33029 0.2944	0.55222 0.0626

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