WEATHER AND PATIENTS

Impact of weather on A&E patient's number

Impact of weather on A&E patient's number

Variable-oriented research design used

This research used variable oriented research design, because the results are driven by using general theories. Based on theories and data, the data is tested and interpreted. Variable-oriented method is used in quantitative technique.

Deductively

The deductive approach is used in this research to reach a specific conclusion from a general research. Marlow (2011, p. 9) explained that quantitative research uses statistical tests for analyzing the data. Quantitative means quantity in amount or measurement. The data collected is in the form of measurement. By analyzing data, it is concluded that whether the hypothesis is accepted or rejected. It further states the similarities and differences between the two variables.

Hypothesis

H0: The weather has a direct impact on the numbers of A&E patients.H1: The weather has an indirect impact on the numbers of A&E patients.Analytical technique used

This research used Multiple Regression Analysis technique to analyze the impact of weather on the number of A&E patients. In addition, Time Series Model was also used, to determine the number of patients visiting throughout the different seasons per year.

Limitation of regression technique

The limitations of regression technique are as follows;

This technique requires quantitative data only and scalar variables are essential for the regression technique. It does not include categorical variables.

The data collection for regression requires time and collecting data from thousands of respondents can be expensive.

The regression technique analysis the strong and direct relationship between two variables, and does not estimate the affect of other variables that are important and significant for the study.

Sometimes, the relationship between dependent variable and independent variables can be globular means dependent variable (Y) explains independent variable (X), and independent variable (X) explains the dependent variable (Y).

This technique requires vast data, to interpret the influence of one variable on other variable. for instance, the impact of impact of television advertisements on purchasing behaviour of customers belonging to 20-30 age group cannot be estimated, because the television advertisements has an affect on other consumers also belonging to different age groups.

Epistemological consideration

This research is based on positivism, where that is authentic sources are actually used for obtaining the data. It uses information that is tested and proven. This research uses statistical method to test the hypothesis and to find a relation between the variables.

Analysis and interpretation of data

The regression technique is used because it makes the data understandable. Furthermore, it is the most appropriate technique when analyzing the impact of one variable on the other variable. After applying the regression technique, I followed this up by analyzing and the interpretation the collected information. From the table below there were two missing values in each independent variable. The missing values were determined by the series mean method. The series mean method replaces the missing values in the data.

Result Variables

Result Variable

N of Replaced Missing Values

Case Number of Non-Missing Values

N of Valid Cases

Creating Function

First

Last

1

temp_1

2

1

2351

2351

SMEAN(temp)

2

wdsp_1

2

1

2351

2351

SMEAN(wdsp)

3

prcp_1

2

1

2351

2351

SMEAN(prcp)

4

sndp_1

2

1

2351

2351

SMEAN(sndp)

The Pearson correlation shows an association between the independent and dependent ...