Presentation is loading. Please wait.

Presentation is loading. Please wait.

Week one Introduction to Statistics Chs 221 Dr. wajed Hatamleh

Similar presentations


Presentation on theme: "Week one Introduction to Statistics Chs 221 Dr. wajed Hatamleh"— Presentation transcript:

1 Week one Introduction to Statistics Chs 221 Dr. wajed Hatamleh
Chapter 1 Population Sample Variable and parameter Variables Post test Dr. Wajed Hatamleh

2 What is Statistics? Statistics is the term for a collection of mathematical methods of organizing, summarizing, analyzing, and interpreting information gathered in a study 2

3 Statistics Data Collection Summarizing Data Interpreting Data
Drawing Conclusions from Data

4 Data Collection Designing experiments Observational studies
Does aspirin help reduce the risk of heart attacks? Observational studies Patient attitude toward saudi nurses

5 Summarizing and Interpreting Data
Grade distribution for a college course ( Growth and development course NUR 353)

6 Drawing Conclusions Quality control and improvement
Analysis of designed experiments Analysis of observational studies

7 Definition Data observations (such as measurements, genders, survey responses) that have been collected Dr. Wajed Hatamleh

8 Definition Population
The complete collection of all elements (scores, people, measurements, and so on) to be studied; the collection is complete in the sense that it includes all subjects to be studied Dr. Wajed Hatamleh

9 Population Examples Unemployment - Status of ALL employable people (employed, unemployed) in the KSA Entry college Scores - scores of EVERY person that took the Entry college in KSA during 2009 Responses of ALL currently enrolled underage college students as to whether they have consumed Arabic Coffee in the last 24 hours

10 Sample A subset of the population data that are actually collected in the course of a study.

11 Sample Examples Unemployment - Status of the 1000 employable people interviewed. College entry Scores - scores of 20 people that took the exam during 2009 Responses of 538 currently enrolled underage college students as to whether they have consumed Arabic coffee in the last 24 hours

12 Population vs. Sample Population Sample

13 WHO CARES? In most studies, it is difficult to obtain information from the entire population. We rely on samples to make estimates or inferences related to the population.

14 Definition population parameter Parameter
a numerical measurement describing some characteristic of a population. population parameter Dr. Wajed Hatamleh

15 Definition sample statistic Statistic
a numerical measurement describing some characteristic of a sample. sample statistic Dr. Wajed Hatamleh

16 Key Terms 1. Population (Universe) 2. Sample 3. Parameter 4. Statistic
All Items of Interest 2. Sample Portion of Population 3. Parameter Summary Measure about Population 4. Statistic Summary Measure about Sample P in Population & Parameter S in Sample & Statistic Data facts or information that is relevant or appropriate to a decision maker Population the totality of objects under consideration Sample a portion of the population that is selected for analysis Parameter a summary measure (e.g., mean) that is computed to describe a characteristic of the population Statistic a summary measure (e.g., mean) that is computed to describe a characteristic of the sample

17 Definition Variable: Is a characteristics of an individual or object,
it can be qualitative or quantitative. Examples: (IQ level, Heart rate, age, gender, height, weight, blood pressure, income, eye color, cholesterol level) Dr. Wajed Hatamleh

18 Qualitative and Quantitative Data( variable)
Data can be further classified as being qualitative or quantitative. The statistical analysis that is appropriate depends on whether the data for the variable are qualitative or quantitative. In general, there are more alternatives for statistical analysis when the data are quantitative.

19 Qualitative Variables ( Data)
Labels or names used to identify an attribute of each element Often referred to as categorical data Can be either numeric or nonnumeric Appropriate statistical analyses are rather limited Examples: Gender, eye color,

20 Quantitative variables (DATA)
Quantitative data indicate how many or how much: discrete, if measuring how many continuous, if measuring how much Quantitative data are always numeric. Examples: Height of nursing student, patient weight and age,

21 Working with Quantitative Data
Quantitative data can further be described by distinguishing between discrete and continuous types. Dr. Wajed Hatamleh

22 Definition Discrete data (i.e. the number of possible values is
result when the number of possible values is either a finite number or a ‘countable’ number (i.e. the number of possible values is 0, 1, 2, 3, . . .) Example Number of siblings: 0, 1, 2, etc. (1.2 is not possible) Number of hospital beds ( beds is not possible Dr. Wajed Hatamleh

23 Definition Continuous (numerical) data
result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps Example: The amount of milk that a cow produces; e.g gallons per day, weight, height. Dr. Wajed Hatamleh

24 Definitions Random Sample
members of the population are selected in such a way that each individual member has an equal chance of being selected Dr. Wajed Hatamleh

25 Sample data must be collected in an appropriate way, such as through a process of random selection.
If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistical torturing can salvage them. Dr. Wajed Hatamleh

26 selection so that each has an
Random Sampling selection so that each has an equal chance of being selected Dr. Wajed Hatamleh

27 Systematic Sampling Select some starting point and then
select every K th element in the population Dr. Wajed Hatamleh

28 use results that are easy to get
Convenience Sampling use results that are easy to get Dr. Wajed Hatamleh

29 Post test time Are you ready? Dr. Wajed Hatamleh

30 A collection of observations.
The population is A collection of observations. A collection of methods for planning studies and experiments. The complete collection of all elements. D. A sub-collection of members drawn from a larger group. Dr. Wajed Hatamleh

31 A collection of observations.
The population is A collection of observations. A collection of methods for planning studies and experiments. The complete collection of all elements. D. A sub-collection of members drawn from a larger group. Dr. Wajed Hatamleh

32 Which is an example of quantitative data?
A. Weights of high school students. B. Genders of actors and actresses. C. Colors of the rainbow. D. Consumer ratings of a particular automobile (below average, average, and above average.) Dr. Wajed Hatamleh

33 Which is an example of quantitative data?
A. Weights of high school students. B. Genders of actors and actresses. C. Colors of the rainbow. D. Consumer ratings of a particular automobile (below average, average, and above average.) Dr. Wajed Hatamleh

34 Which is not an example of continuous data?
A. Temperature on a thermometer. B. Number of students in an algebra class. C. Mean weight of 100 flour sacks. D. Amount of water pumped from a pond per day. Dr. Wajed Hatamleh

35 Which is not an example of continuous data?
A. Temperature on a thermometer. B. Number of students in an algebra class. C. Mean weight of 100 flour sacks. D. Amount of water pumped from a pond per day. Dr. Wajed Hatamleh

36 End of Chapter 1


Download ppt "Week one Introduction to Statistics Chs 221 Dr. wajed Hatamleh"

Similar presentations


Ads by Google