Question

Question: To what extent does gender influence length of hospital stay for MI patients ?

Information on data set
Which variables are you investigating?	ID Length of hospital stay Gender
What is the type of each variable?	Numeric/Qualitative Quantitative Normal
List the descriptive stats you will run on the data.	Distribution Central Tendencies: Mean, Std, Dev, Mode, Median, Min, Max etc.
What does each calculation tell you about the data?	65 Males, 35 Females The average LOS for males = 6.3 days The average LOS for females = 7.8 days 5 days was the mode for males 4 days was the mode for females
	0= Male 1= Female

1. Assess the collected data. Use this section to layout the source, parameters, and any limitations of your data. Specifically, you should:

1. Describe the key features of your data set. Be sure to assess how these features affect your analysis.
2. Analyze the limitations of the data set you were provided and how those limitations might affect your findings. Justify your response.

Answer 1

MALES:

Total No.of Males=65

Avg. LOS (Male)=6.3 days

Mode (Male) =5 days

so, calculating

Median(Male) =(Mode+2Mean)/3 =(5+ 2X6.3)/3=18.6/3= 6.2

FEMALES:

Total no. of Females= 35

Avg. LOS (Female)= 7.8 days

Mode (Female)= 4 days

Median (Female) = (4+2X7.8)/3 = 6.5333 days

The data is a qualitative data as the whole dataset information is not given. The no. of females is 35 having an avg LOS of 7.8 days which is greater than the avg LOS of the 65 no.of males which implies that females are more likely to stay more in the hospital.Also when median is taken into concern then also the females are having greater median which implies that females are more likely to stay in hospital for longer time.

Thus gender influences to a certain extent the length of hospital stay .

The source of this dataset is the length of hospital stay for MI patients and the regulating parameter is the gender of the patient.

The limitations may be listed as follows,

1. The total dataset information is not given. The record of each and every of the 100 patients taken into account , record of their individual length of stay would help to decide the maximum ,minimum and even the range of LOS of the patient and also the central tendencies and standard deviation of the data and a better study could had been made to analyse the fact of gender influencing the length of stay of patients in the hospital.

2. We could have also determined which distribution the datatset follows if the whole record was given.

Findngs:

1.The mean median and mode of the distribution are not equal, so the dataset is not symmetrically distributed, which also implies that the distribution is not normal as well.

2.It is a bimodal distribution(it have two peaks as it have two modes)

3. the dataset have unequal no. of observations in male and female categories which is also a limitation.