Introduction to Reseach NUR301C2

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Introduction to Reseach NUR301C2

• Statistics Computer Laboratory Classes
• Dr. Bryan Scotney
• Room D070
• bw.scotney_at_ulst.ac.uk

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Introduction to the Module

• Lecture Contents
• 1. Introduction to Statistics (L1)
• 2. Data and Variables (L1)
• 3. Describing a Sample (L2)
• 4. Summary statistics for Frequency Data (L2)
• 5. Summary statistics for Numerical Data (L3)
• 6. Cross-tabulation and Data Coding (L4)
• 7. Relationships between Numerical Variables (L5)
• Lab Exercises
• Frequency data, Describing samples, Contigency
  tables and association, correlation
• Assessment
• Computer-based Class Test Assignment

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Introduction to the Module

• Reference Books and Research Papers
• For part of the Advance Reading you will need to
  acquire copies of the following papers from the
  library
• Thompson, D.R. Cordle, C.J., Support of wives
  of myocardial infarction patients, Jnl. of
  Advanced Nursing, Vol 13, pp 223-228, (1988).
• Rukholm, E., Bailey, P., Coutu-Wakulczyk, G.
  Bailey, W.B., Needs and Anxiety levels in
  relatives of intensive care unit patients, Jnl.
  of Advanced Nursing, Vol 16, pp 920-928, (1991).
• Brocklehurst, J.C., Morris, P., Andrews, K.,
  Richards, B. Laycock, P., Social effects of
  stroke, Soc. Sci. Med., Vol 15A, pp 35-39,
  (1981).
• The two books referred to under Advance Reading
  are
• Reid, N.G., Health Care Research by Degrees,
  Blackwell (1993)
• Reid, N.G. Boore, J.P.R., Research Methods and
  Statistics in Health Care, Edward Arnold (1987).
• Module Plan and Timetable

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Introduction to the Computer Labs

• Laboratory Location
• South Building, D Block, Room D072 and D075
• Network username and password
• To be available on your first day
• Log on to computer network
• Enter your username and password
• Press Enter or click OK
• Windows 95 is then loaded
• Log out from computer network
• Click Start at the left-bottom part of the screen
• Then click Shutdown
• On the Shutdown window, choose Close all programs
  and log on as a different user
• Click Yes

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Introduction to the Minitab

• Minitab an easy-to-use statistical computing
  package
• Originally designed in 1972 for students in
  introductory statistics courses in Pennsylvania
  State University
• Now used by engineers, social and physical
  scientists, managers and others who have to
  organise and analyse data
• To Start Minitab...
• Click the Windows 95 Start
• Select DOS Application, and then Minitab
• To Use Minitab...
• The minitab prompt is MTBgt
• Enter commands at the command screen
• Create, edit, and view data on the worksheet
  screen
• To Exit from Minitab...
• In the command mode, enter Stop

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Introduction to Minitab

• Some Minitab commands
• stop exit Minitab
• restart clears all data
• info lists information about the data
• retr retrieves data from a file
• desc describes the data with summary statistics
• hist draws a histogram and gives frequency data
• tally gives the frequencies for a variable
• table gives frequencies of values in a column
• code coding columns
• name naming a column
• unstack creates new columns by dividing up some
  columns into groups according to another column.
• corr chisquare let plot dotplot

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Introduction to QMark

• Qmark
• Question Mark is a computer program, which can be
  used to create and deliver tests, exams and other
  kinds of assessments on a computer.
• This package is to be used for tutorials and
  final class test
• Start the Qmark
• Click the Windows 95 Start
• Select DOS Application, then Qmark
• Enter your surname and forename, e.g. Smith,
  Nicola
• Answer questions
• With each question there will be instructions on
  how to choose an answer
• e.g. Enter a number from 1 to 5 Enter a letter
  from A to F Type in any number and press Enter
  Select several letters and finish by pressing
  F10.
• Exit from Qmark
• Press ESC at the end of a tutorial or a test

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1. Introduction to Statistics

• The topic of statistics relates to all aspects of
  
• designing and carrying out surveys
• representing the collected data in a graphical
  form
• summarising the data
• applying statistical tests to the data to see
  what conclusions can be drawn
• In this course we will focus on
• the principles underlying descriptive statistics
• choosing appropriate statistical techniques
• how to use these techniques

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2. Data and Variables

• Reading RB pp49-50, R pp56-70
• 2.1 Statistical terms
• In a statistical experiment you select a sample
  from the population you want to say something
  about. You collect data corresponding to the
  chosen variables from each individual in the
  sample. Using the data from the sample you might
  then make some conclusions about the whole
  population.
• Example 1
• Among all GPs in N. Ireland (x) you pick two
  from each county (y) and determine how many years
  of experience (z) each has had in a hospital.
• population x
• sample y
• variable z

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2.1 Statistical Terms

• Example 2
• Pick casualty cases in a hospital at random and
  determine if the case requires (1)immediate
  surgery, (2)non-immediate surgery, (3)nurse
  treatment or (4)only a prescription or (5)no
  treatment or prescription.
• Population casualty cases
• sample picked at random
• variable the case requirement
• data to collect, each has a value from 1,5
• possible conclusion a very high percentage
  requires nurse treatment or only a prescription,
  but very few need immediate surgery or no
  treatment or prescription.
• possible conclusion It is the normal case that
  a patient requires immediate surgery.

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2.1 Statistical Terms

• The population
• is not always people. It is simply the collection
  of all things (from which you pick a sample)
  about which you want to say something
• For example, it could be the collection of all
  cancer types, reported incidences of theft of
  patients property, etc.
• The Sample
• When picking the sample it is (usually)
  important that the sample be picked randomly from
  the population, i.e. each individual of the
  population is as likely as any other to be picked
  for the sample.
• For example, if you want to estimate the
  percentage of female patients in a hospital you
  should not simply pick as your sample all
  patients in the surgery and maternity wards.

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2.2 Types of Data

• Categorical Data
• Nominal
• The lowest level of measurement.
• Subjects are assigned to categories
• No hierarchical relationship between categories
• Ordinal
• Subjects are assigned to ranked categories
  (grade)
• A clear hierarchy across categories
• The distances between categories are not
  specified

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2.2 Types of Data

• Examples of nominal data
• order of the categories is unimportant
• gender male1 female2
• birthplace N.Ireland1 Irish Rep.2 Britain3
  
• Other EC4 Non-EC5
• Examples of Ordinal data
• the categories are ordered (e.g. lowest to
  highest)
• Academic Post
• Lecturer1 Senior Lecturer2 Reader3
  Professor4
• Level of agreement
• Agree1 Don't Know2 Disagree3
• (e.g. you asked the question "indicate your level
  of agreement with the statement 'nurses earn too
  much'")

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2.2 Types of Data

• Numerical Data
• Interval
• Subjects are placed in ordered categories
• The distances between categories is known, and no
  true zero
• Ratio
• The highest level of measurement
• data comes from an actual measurement

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2.2 Types of Data

• Examples of interval data
• data in ordered categories and interval is known
• Temprature measured on the Fahrenheit scale
• We say 600F is 300F hotter than 300F
• We always have a temperature
• We do not say 600F is twice as hot as 300F
• There is no true zero. The zero we have got is
  arbitrarily set.
• Examples of ratio data
• data comes from an actual measurement
• pulse rate (pulses per minute)
• daily intake of fibre (in grams)
• weight (in kgs)

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2.2 Types of Data

• Variables
• Data is collected on the chosen variables
• Apart from the level of measurement, all
  variables are either Discrete or Continuous
• Discrete
• the variable can take one of a limited number of
  values. Categorical data (nominal or ordinal) are
  discrete
• Continuous
• the variable can take any value in a range on a
  continuous scale. Interval and ratio data are
  continuous

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2.2 Types of Data

• Exercises
• For each of the following say whether it is
  nominal, ordinal or ratio
• Primary level in school is a ____________
  variable
• Tax-free allowance is a _____________ variable
• Floor level of wards is a ____________ variable.
• For each of the following say whether it is
  nominal, ordinal or ratio and also whether it is
  discrete or continuous.
• tax rate is ____________ and ___________.
• shoe size is ____________ and ___________.
• number of accidents in a ward is ________ and
  __________.
• prescribed grams of keradytone is ________ and
  _________.
• relationship of visitor is _______ and
  __________.