Docstoc

descriptive statistic

Document Sample
descriptive statistic Powered By Docstoc
					Assignment 1A




1. Define descriptive statistics.


       Descriptive statistics is one of the branches of statistics that involves counting,
measuring, describing, ordering and census taking sets of data. It is used for simplifying
and summarizing basic information. In descriptive statistics, there are two variable which
are qualitative variable (categorical) and quantitative variable (numerical).




2. State the purpose of conducting descriptive statistics.


   a) To give clear view of raw data.
   b) To describe what the data shows in easy and simplest way.
   c) To present quantitative descriptions in a manageable form.




3. Describe type of descriptive statistics.


       Descriptive statistics have two type which are quantitative (numerical) and
qualitative (categorical). Quantitative (numerical) type of descriptive statistics that can
be measure. Unit of measurement can be either discrete or continuous. Discrete
measurement gives a meaning that the things that are going to be measure can be
counted. Values that are going to be measure are a whole number with no decimal.
       Discrete measurement is characterized by gaps or interruptions in the values. An
example of discrete measurement (variable) is number of second year nursing students on
2010. Discrete measurement has two measurement scales which are nominal and ordinal.
Whereas continuous measurement includes interval and ratio scales with no gaps or
interruptions within a specific interval and it also have decimal. For example, height,
weight and time of death.
       Back to quantitative variable for descriptive statistics, there are two scales for
measurement for quantitative variable which are interval and ratio. For interval scale,
there is no true zero. Meaning that the zero is arbitrary or no absolute zero. The distance
between values is equal. This make this scale can easily be added or subtract. An
example of interval scale is temperature and IQ score.
       For example, differences between 40 °C and 50 °C same as the difference
between 50 °C and 60 °C. This shows that the distance between values is equal. Another
example is 0 °C does not mean that there is no heat. This shows that interval scale have
an arbitrary zero. But it needs to be note that in interval scale, ratio between numbers is
not meaningful. For example, a person with IQ score of 100 is not twice as high as
person with IQ 50.
       For ratio scale of measurement, it has true zero which represents the absence of
the characteristics. Not like interval scale that has zero which does not represent the
characteristics. Just like the interval scale, ratio scale also has distance between values.
This makes it able to be divided or multiply. Not like interval scale, ratios between
numbers for ratio measurement scale are meaningful. For example, person with weight
of 100kg as heavy as two person with weight of 50kg per person. Examples of ratio scale
are weight, height, blood pressure, number of children, income and many more.
       Another type of descriptive statistics is the qualitative (categorical). Qualitative is
characterized as variable that are merely categorized. Unit of measurement is not
numeric. For categorical variable, there are two types of scale measurement which are the
nominal and ordinal. Nominal scale is the lowest scale of measurement. The data is
mutually exclusive, meaning that there is no overlapping between data. The data is not
rank in order. For example, sex (male, female). We cannot rank the sex and there is no
overlapping between sexes. Another example is race (Malay, Chinese, Indian), type of
disease (infectious disease, non-infectious disease) and more.
       Not like nominal, ordinal scale can be rank into categories. The data can be
arranged from lowest to highest or vice versa. The data is mutually exclusive. For
example socioeconomic status. We can rank socioeconomic status into low, middle and
high based on the income of a person or family per month and education level of a
person. Another example is the severity of a disease. We can order it into mild,
moderate and severe based on patient’s condition.


Assignment 1B

4. Analyze and fill in the blank.

      a) Slide 17


                    Variables                               Frequency (%)
Sex
  Female                                                       34 (66.7)
  Male                                                         17 (33.3)
Smoking
  Yes                                                          13 (25.5)
  No                                                           37 (72.5)
DM
  Yes                                                           5 (9.8)
  No                                                           44 (86.3)
ACT group ª
  Total control                                                 1 (2.0)
  Well control                                                 11 (21.6)
  Not control                                                  39 (76.5)



      b) Slide 21


           Variables                                Frequency (%)
                                         Female                            Male
Smoking
  Yes                                     0 (0)                       13 (81.3)
  No                                    34 (100)                       3 (18.8)
DM
  Yes                                    2 (6.3)                       3 (17.6)
  No                                    30 (93.8)                     14 (82.4)
ACT group ª
  Total control                           1 (2.9)                        0 (0)
  Well control                           7 (20.6)                      4 (23.5)
  Not control                           26 (76.5)                     13 (76.5)
c) Slide 37


         Variables     Mean (SD)                   Median (IQR)

Age (year)            45.8 (15.74)                      -

Weight (kg)           60.1 (15.13)                      -

Height (cm)                                             -
                      156.8 (7.82)


ACT (score)                -                         3.00 (1)




d) Slide 43



         Variables                     Mean (SD)

                        Female                         Male
Age (year)           45.47 (16.889)                   50 (19)

Weight (kg)          57.91 (15.968)                   64 (14)

Height (cm)          154.13 (27.855)                162.50 (11)

ACT (score)             3.00 (1)                     3.00 (1)
e) Slide 67



      Variables     Mean (SD)      Median (IQR)    n (%)
Age (year)          45.8 (15.74)        -
Sex                                               34 (66.7)
   Female                                         17 (33.3)
   Male

Smoking status
  Yes                                             13 (25.5)
  No                                              37 (72.5)

Diabetes Mellitus
  Yes                                              5(9.8)
  No                                              44 (86.3)

Weight (kg)         60.1 (15.13)                  51(100)
Height (cm)         156.8 (7.82)                  48 (94.1)
ACT (score)                          3.00 (1)     51 (100)
ACT group
  Total control                                    1 (2.0)
  Well control                                    11 (21.6)
  Not control                                     39 (76.5)
            GTB 302/3
         BIOSTATISTICS

     ASSIGNMENT 1A & 1B:
    DESCRIPTIVE STATISTICS

  NAME: Nazilatul Hidayah Jusoh
      MATRIC NO:101470
      COURSE: Nursing 2
LECTURER: Dr. Aniza Binti Abd. Aziz
 DATE OF SUBMISSION: Sunday,
       January 31st , 2010

				
DOCUMENT INFO