Question

1. The Stock Price details of TATA TELESERVICES (MAHARASHTRA) LTD. are

given below

Date Close

Date                     Close          No. of Shares    No of Trades     Total Turnover

res es

01-03-2019          3.09                69,242               100                   2, 14,257

05-03-2019           3.35              1, 97,344              251                   6, 51,621

06-03-2019           3.41              1, 58,205              160                   5, 47,942

07-03-2019           3.55              4, 00,183              433                 13, 99,537

08-03-2019           3.49              2, 73,890              503                   9, 42,944

11-03-2019             3.5              1, 46,178              145                   5, 12,714

12-03-2019           3.52                 80,672              109                    2, 83,868

13-03-2019           3.46              1, 49,428              116                   5, 14,536

14-03-2019          3.4                  72,539             183                   2, 44,876

For the above sample, determine the following measures:

a. The mean closing price

b. The standard deviation of total number of shares

c. The median value of number of trades

d. The 75th percentile value of total turnover

Analyze the above data using descriptive statistics and comment on the relationship between the various variables

Answer 1

Date	Close	No._of_Shares	No_of_Trades	Total_Turnover
01-03-2019	3.09	69242	100	214257
05-03-2019	3.35	197344	251	651621
06-03-2019	3.41	158205	160	547942
07-03-2019	3.55	400183	433	1399537
08-03-2019	3.49	273890	503	942944
11-03-2019	3.5	146178	145	512714
12-03-2019	3.52	80672	109	283868
13-03-2019	3.46	149428	116	514536
14-03-2019	3.4	72539	183	244876

Mean of Close =3.14889

Sd of No of share = 107964.4.

Median of No. of trades is given in the summary. =160.0

75Th percentile of Total Turnover = 651621

# Correlation panel
panel.cor <- function(x, y){
usr <- par("usr"); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- round(cor(x, y), digits=2)
txt <- paste0("R = ", r)
cex.cor <- 0.8/strwidth(txt)
text(0.5, 0.5, txt, cex = cex.cor * r)
}
# Customize upper panel
upper.panel<-function(x, y){
points(x,y, pch = 19)
}
# Create the plots
pairs(data[,2:5],
lower.panel = panel.cor,
upper.panel = upper.panel)

> mean (data$Close) [1] 3.418889 > sd (data$No._of_Shares) [1] 107964.4 summary(dataSNo_of Trades) Min. 1st Qu. Meian Mean 3rd Qu Max 100.0 116.0 160.0 222.2251.0503.0 >quantile(dataSTotal_Turnover,0.75) 75% 651621

00000 200000 300000 200000 400000 600000 800000 1000000 400000 R·0.86 R=1 R- 0.85 31 32 3334 35 3.5 100 200 300 400 500