SlideShare una empresa de Scribd logo
1 de 10
Key GCSE Statistics Notes Primary Data: Data collected by person going to use it. Advantage: Accuracy known Disadvantage: Time consuming Secondary Data Data  not  collected by the person going to use it. Advantage: Easy to get/Cheap Disadvantage: Accuracy unknown
Key GCSE Statistics Notes Population: Everybody or everything that could be involved in the investigation. Census: Data about every member of the population Advantage: Unbiased/Accurate Disadvantage: Time consuming
Key GCSE Statistics Notes Sample: Only part of the population used in an investigation. Advantage: Less Time/Cheaper/Easier Disadvantage: Possibly biased
Key GCSE Statistics Notes Interview: Advantage: Detailed answers/Lots of questions asked Disadvantage: Expensive Questionnaire Advantage: Cheaper Disadvantage: Answers less detailed   Possible poor response rate
Key GCSE Statistics Notes Pilot Survey: A small scale of the questionnaire to be used Advantage: Shows you likely responses Checks questions are suitable Allows you to tweak/alter /add questions if  needed
Types of Data: Quantitative  variables: Qualitative  variables: These have  numerical  observations, such as  shoe size (7, 8, 9, 7.5, 8.5) Height (178cm, 1.9m) and weight. Variables that have non-numerical observations, eg.  Eye colour , Favourite food
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Quantitative  variables can be broken down further. Quantitative  variables: Continuous data Discrete data … Are measured on a scale and can take any value eg.  height The units of measurement (eg. CDs)  cannot  be split up; there is nothing between 1 CD and 2 CDs.
Decide whether or not the following are continuous or discrete: a) Shoe size:  b) Gender:  c)  The numbers of chocolates in a box :  d) T imes taken for athletes to run 100m: Discrete because can only take specific values, eg, 7, 8, 8.5. Cannot get a size 8.35 Discrete because can only be male or female. Discrete. Time is  continuous Statistics
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Más contenido relacionado

La actualidad más candente

Inferential statistics (2)
Inferential statistics (2)Inferential statistics (2)
Inferential statistics (2)
rajnulada
 
Sampling techniques
Sampling techniquesSampling techniques
Sampling techniques
chetan1923
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
Aileen Balbido
 

La actualidad más candente (20)

Data collection,tabulation,processing and analysis
Data collection,tabulation,processing and analysisData collection,tabulation,processing and analysis
Data collection,tabulation,processing and analysis
 
Scales of measurment
Scales of measurmentScales of measurment
Scales of measurment
 
Data
DataData
Data
 
Systematic ranom sampling for slide share
Systematic ranom sampling for slide shareSystematic ranom sampling for slide share
Systematic ranom sampling for slide share
 
Inferential statistics (2)
Inferential statistics (2)Inferential statistics (2)
Inferential statistics (2)
 
presentation of data
presentation of datapresentation of data
presentation of data
 
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
Data Collection (Methods/ Tools/ Techniques), Primary & Secondary Data, Quali...
 
Basic Concepts of Statistics - Lecture Notes
Basic Concepts of Statistics - Lecture NotesBasic Concepts of Statistics - Lecture Notes
Basic Concepts of Statistics - Lecture Notes
 
Introduction to spss
Introduction to spssIntroduction to spss
Introduction to spss
 
Classification of data
Classification of dataClassification of data
Classification of data
 
Data analysis and Presentation
Data analysis and PresentationData analysis and Presentation
Data analysis and Presentation
 
Presentationofdata
PresentationofdataPresentationofdata
Presentationofdata
 
Introduction to Statistics - Basic concepts
Introduction to Statistics - Basic conceptsIntroduction to Statistics - Basic concepts
Introduction to Statistics - Basic concepts
 
Basics stat ppt-types of data
Basics stat ppt-types of dataBasics stat ppt-types of data
Basics stat ppt-types of data
 
Introduction to Statistics
Introduction to StatisticsIntroduction to Statistics
Introduction to Statistics
 
Sampling techniques
Sampling techniquesSampling techniques
Sampling techniques
 
Non probability sampling
Non probability samplingNon probability sampling
Non probability sampling
 
What is statistics
What is statisticsWhat is statistics
What is statistics
 
probability and non-probability samplings
probability and non-probability samplingsprobability and non-probability samplings
probability and non-probability samplings
 
Descriptive statistics
Descriptive statisticsDescriptive statistics
Descriptive statistics
 

Destacado

Introduction To Statistics
Introduction To StatisticsIntroduction To Statistics
Introduction To Statistics
albertlaporte
 
Data displays in statistics
Data displays in statisticsData displays in statistics
Data displays in statistics
annieg8989
 
Unit 1 powerpoint
Unit 1 powerpointUnit 1 powerpoint
Unit 1 powerpoint
forestmad1
 
Unit 1 research methods tmanston
Unit 1 research methods tmanstonUnit 1 research methods tmanston
Unit 1 research methods tmanston
mdrummond13
 
Statistics Vocabulary Chapter 1
Statistics Vocabulary Chapter 1Statistics Vocabulary Chapter 1
Statistics Vocabulary Chapter 1
Debra Wallace
 
Data type source presentation im
Data type source presentation imData type source presentation im
Data type source presentation im
Mohmmedirfan Momin
 
Introduction to business statistics
Introduction to business statisticsIntroduction to business statistics
Introduction to business statistics
Aakash Kulkarni
 

Destacado (20)

Introduction To Statistics
Introduction To StatisticsIntroduction To Statistics
Introduction To Statistics
 
Basic Statistical Concepts and Methods
Basic Statistical Concepts and MethodsBasic Statistical Concepts and Methods
Basic Statistical Concepts and Methods
 
Data displays in statistics
Data displays in statisticsData displays in statistics
Data displays in statistics
 
5 Tips to Make you a Survey Measurement Rock Star
5 Tips to Make you a Survey Measurement Rock Star5 Tips to Make you a Survey Measurement Rock Star
5 Tips to Make you a Survey Measurement Rock Star
 
Unit 1 powerpoint
Unit 1 powerpointUnit 1 powerpoint
Unit 1 powerpoint
 
Unit 1
Unit 1Unit 1
Unit 1
 
Unit 1 research methods tmanston
Unit 1 research methods tmanstonUnit 1 research methods tmanston
Unit 1 research methods tmanston
 
Unit 1
Unit 1Unit 1
Unit 1
 
Ibm spss statistics 19 brief guide
Ibm spss statistics 19 brief guideIbm spss statistics 19 brief guide
Ibm spss statistics 19 brief guide
 
International financial management working notes
International financial management working notesInternational financial management working notes
International financial management working notes
 
Statistics Vocabulary Chapter 1
Statistics Vocabulary Chapter 1Statistics Vocabulary Chapter 1
Statistics Vocabulary Chapter 1
 
Survey data & sampling
Survey data & samplingSurvey data & sampling
Survey data & sampling
 
Data type source presentation im
Data type source presentation imData type source presentation im
Data type source presentation im
 
Introduction to business statistics
Introduction to business statisticsIntroduction to business statistics
Introduction to business statistics
 
Introduction to Business Statistics
Introduction to Business StatisticsIntroduction to Business Statistics
Introduction to Business Statistics
 
Lecture 2: Preliminaries (Understanding and Preprocessing data)
Lecture 2: Preliminaries (Understanding and Preprocessing data)Lecture 2: Preliminaries (Understanding and Preprocessing data)
Lecture 2: Preliminaries (Understanding and Preprocessing data)
 
Comparative study of eCommerce portals - jabong, yebhi, myntra
Comparative study of eCommerce portals - jabong, yebhi, myntraComparative study of eCommerce portals - jabong, yebhi, myntra
Comparative study of eCommerce portals - jabong, yebhi, myntra
 
Presentation of data
Presentation of dataPresentation of data
Presentation of data
 
Mba i qt unit-1_basic quantitative techniques
Mba i qt unit-1_basic quantitative techniquesMba i qt unit-1_basic quantitative techniques
Mba i qt unit-1_basic quantitative techniques
 
001 Lesson 1 Statistical Techniques for Business & Economics
001 Lesson 1 Statistical Techniques for Business & Economics001 Lesson 1 Statistical Techniques for Business & Economics
001 Lesson 1 Statistical Techniques for Business & Economics
 

Similar a Statistics Notes

Business Research Methods. data collection preparation and analysis
Business Research Methods. data collection preparation and analysisBusiness Research Methods. data collection preparation and analysis
Business Research Methods. data collection preparation and analysis
Ahsan Khan Eco (Superior College)
 
MATH 106 QUIZ 6NAME _____ _________________ Professor Dr. K.docx
MATH 106 QUIZ 6NAME _____ _________________  Professor Dr. K.docxMATH 106 QUIZ 6NAME _____ _________________  Professor Dr. K.docx
MATH 106 QUIZ 6NAME _____ _________________ Professor Dr. K.docx
andreecapon
 
Measurement
MeasurementMeasurement
Measurement
wilsone
 
2012 data analysis
2012 data analysis2012 data analysis
2012 data analysis
cherylyap61
 
Survey Design Ii 1204634497987472 5
Survey Design Ii 1204634497987472 5Survey Design Ii 1204634497987472 5
Survey Design Ii 1204634497987472 5
Liz Smith
 

Similar a Statistics Notes (20)

Survey & Questionnaire Design in Applied Marketing Research
Survey & Questionnaire Design in Applied Marketing ResearchSurvey & Questionnaire Design in Applied Marketing Research
Survey & Questionnaire Design in Applied Marketing Research
 
Business Research Methods. data collection preparation and analysis
Business Research Methods. data collection preparation and analysisBusiness Research Methods. data collection preparation and analysis
Business Research Methods. data collection preparation and analysis
 
Ch01sp10
Ch01sp10Ch01sp10
Ch01sp10
 
Introduction To Six Sigma
Introduction To  Six  SigmaIntroduction To  Six  Sigma
Introduction To Six Sigma
 
Chapter1
Chapter1Chapter1
Chapter1
 
Business Statistics Chapter 1
Business Statistics Chapter 1Business Statistics Chapter 1
Business Statistics Chapter 1
 
MATH 106 QUIZ 6NAME _____ _________________ Professor Dr. K.docx
MATH 106 QUIZ 6NAME _____ _________________  Professor Dr. K.docxMATH 106 QUIZ 6NAME _____ _________________  Professor Dr. K.docx
MATH 106 QUIZ 6NAME _____ _________________ Professor Dr. K.docx
 
problem
problemproblem
problem
 
Measurement
MeasurementMeasurement
Measurement
 
Penggambaran Data dengan Grafik
Penggambaran Data dengan GrafikPenggambaran Data dengan Grafik
Penggambaran Data dengan Grafik
 
Data Collection, Sampling, Measurement Concept, Questionnaire Designing-Types
Data Collection, Sampling, Measurement Concept, Questionnaire Designing-TypesData Collection, Sampling, Measurement Concept, Questionnaire Designing-Types
Data Collection, Sampling, Measurement Concept, Questionnaire Designing-Types
 
Malimu intro to surveys
Malimu intro to surveysMalimu intro to surveys
Malimu intro to surveys
 
2012 data analysis
2012 data analysis2012 data analysis
2012 data analysis
 
10NTC - Data Superheroes - DiJulio
10NTC - Data Superheroes - DiJulio10NTC - Data Superheroes - DiJulio
10NTC - Data Superheroes - DiJulio
 
Survey Design Ii 1204634497987472 5
Survey Design Ii 1204634497987472 5Survey Design Ii 1204634497987472 5
Survey Design Ii 1204634497987472 5
 
Mb0050 research methodology (1)
Mb0050   research methodology (1)Mb0050   research methodology (1)
Mb0050 research methodology (1)
 
Data collection ppt @ bec doms
Data collection ppt @ bec domsData collection ppt @ bec doms
Data collection ppt @ bec doms
 
Introduction to standard setting (cutscores)
Introduction to standard setting (cutscores)Introduction to standard setting (cutscores)
Introduction to standard setting (cutscores)
 
Making sense of numbers - a half-day workshop
Making sense of numbers - a half-day workshopMaking sense of numbers - a half-day workshop
Making sense of numbers - a half-day workshop
 
Sampling brm chap-4
Sampling brm chap-4Sampling brm chap-4
Sampling brm chap-4
 

Último

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
QucHHunhnh
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
PECB
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
SoniaTolstoy
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Krashi Coaching
 

Último (20)

Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
APM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across SectorsAPM Welcome, APM North West Network Conference, Synergies Across Sectors
APM Welcome, APM North West Network Conference, Synergies Across Sectors
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
fourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writingfourth grading exam for kindergarten in writing
fourth grading exam for kindergarten in writing
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 

Statistics Notes

  • 1. Key GCSE Statistics Notes Primary Data: Data collected by person going to use it. Advantage: Accuracy known Disadvantage: Time consuming Secondary Data Data not collected by the person going to use it. Advantage: Easy to get/Cheap Disadvantage: Accuracy unknown
  • 2. Key GCSE Statistics Notes Population: Everybody or everything that could be involved in the investigation. Census: Data about every member of the population Advantage: Unbiased/Accurate Disadvantage: Time consuming
  • 3. Key GCSE Statistics Notes Sample: Only part of the population used in an investigation. Advantage: Less Time/Cheaper/Easier Disadvantage: Possibly biased
  • 4. Key GCSE Statistics Notes Interview: Advantage: Detailed answers/Lots of questions asked Disadvantage: Expensive Questionnaire Advantage: Cheaper Disadvantage: Answers less detailed Possible poor response rate
  • 5. Key GCSE Statistics Notes Pilot Survey: A small scale of the questionnaire to be used Advantage: Shows you likely responses Checks questions are suitable Allows you to tweak/alter /add questions if needed
  • 6. Types of Data: Quantitative variables: Qualitative variables: These have numerical observations, such as shoe size (7, 8, 9, 7.5, 8.5) Height (178cm, 1.9m) and weight. Variables that have non-numerical observations, eg. Eye colour , Favourite food
  • 7.
  • 8. Quantitative variables can be broken down further. Quantitative variables: Continuous data Discrete data … Are measured on a scale and can take any value eg. height The units of measurement (eg. CDs) cannot be split up; there is nothing between 1 CD and 2 CDs.
  • 9. Decide whether or not the following are continuous or discrete: a) Shoe size: b) Gender: c) The numbers of chocolates in a box : d) T imes taken for athletes to run 100m: Discrete because can only take specific values, eg, 7, 8, 8.5. Cannot get a size 8.35 Discrete because can only be male or female. Discrete. Time is continuous Statistics
  • 10.