Data analysis

Data analysis

Data analysis

Sampling Procedure

It is incumbent on the researcher to clearly define the target population. There are no strict rules to follow, and the researcher must rely on logic and judgment. The population is defined in keeping with the objectives of the study.

Sometimes, the entire population will be sufficiently small, and the researcher can include the entire population in the study. This type of research is called a census study because data is gathered on every member of the population.

Usually, the population is too large for the researcher to attempt to survey all of its members. A small, but carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.

Sampling methods are classified as either probability or nonprobability. In probability samples, each member of the population has a known non-zero probability of being selected. Probability methods include random sampling, systematic sampling, and stratified sampling. In nonprobability sampling, members are selected from the population in some nonrandom manner. These include convenience sampling, judgment sampling, quota sampling, and snowball sampling. The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error. In nonprobability sampling, the degree to which the sample differs from the population remains unknown.

Simple Random Sample

To select 10 companies out of total 24 companies we have used random sampling.

Simple random sampling refers to a sampling method that has the following properties.

The population consists of N objects.

The sample consists of n objects.

All possible samples of n objects are equally likely to occur.

The main benefit of simple random sampling is that it guarantees that the sample chosen is representative of the population. This ensures that the statistical conclusions will be valid.

There are many ways to obtain a simple random sample. One way would be the lottery method. Each of the N population members is assigned a unique number. The numbers are placed in a bowl and thoroughly mixed. Then, a blind-folded researcher selects n numbers. Population members having the selected numbers are included in the sample.

The selected companies are:

1

Abcam PLC

2

Antisoma PLC

3

Ark Therapeutics Group PLC

4

Immupharma PLC

5

Kiotech International PLC

6

Osmetech PLC

7

Regen Therapeutics PLC

8

Reneuron Group PLC

9

Senetek PLC

10

Vernalis PLC

Graphical representation for the Close Price

From the above graph it can be found out that that there is increasing trend.

It can be seen that there is a increasing trend in the close price for this company.

there is a decreasing trend in this data set.

It can be seen that there is decreasing trend in this data set.

There is not such an obvious trend in this data set.

Again in this data set it can be seen that there is no trend.

From the above graph it can be seen that that there is an decreasing trend.

Descriptive statistics

Descriptive Statistics

N

Minimum

Maximum

Sum

Mean

Std. Deviation

Variance

Antisoma

60

14.00

53.25

1662.75

27.7125

9.14535

83.637

Ark

60

14.50

149.02

4959.52

82.6587

32.60473

1.063E3

Immupharma

60

42.50

111.75

3838.00

63.9667

16.49618

272.124

Kiotech

56

.88

11.00

246.77

4.4066

2.30798

5.327

Osmetech

60

1.88

30.00

977.21

16.2868

9.14804

83.687

Regen

60

2.13

187.50

4234.16

70.5693

55.91218

3.126E3

Reneuron

54

2.75

40.00

783.57

14.5106

9.33517

87.145

Senetek

60

.90

3.20

108.43

1.8072

.52022

.271

Vernalis

60

1.00

999.76

1.44E4

2.4063E2

367.14619

1.348E5

Valid N (listwise)

54

The above table provides descriptive statistics for all the ...