MATHS CORE AND OPTIONAL ASSESSMENT STANDARDS Found in the Subject Assessment Guidelines (SAG) Dated January 2008.

Slides:



Advertisements
Similar presentations
Rubric Unit Plan Univariate Bivariate Examples Resources Curriculum Statistically Thinking A study of univariate and bivariate statistics.
Advertisements

Chapter 3, Numerical Descriptive Measures
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Measures of Dispersion
Introduction to Summary Statistics
IB Math Studies – Topic 6 Statistics.
The controlled assessment is worth 25% of the GCSE The project has three stages; 1. Planning 2. Collecting, processing and representing data 3. Interpreting.
Chapter 13 Conducting & Reading Research Baumgartner et al Data Analysis.
Descriptive Statistics A.A. Elimam College of Business San Francisco State University.
Analysis of Research Data
1 Business 260: Managerial Decision Analysis Professor David Mease Lecture 1 Agenda: 1) Course web page 2) Greensheet 3) Numerical Descriptive Measures.
B a c kn e x t h o m e Classification of Variables Discrete Numerical Variable A variable that produces a response that comes from a counting process.
Chapter 19 Data Analysis Overview
Measures of Dispersion
Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall 18-1 Chapter 18 Data Analysis Overview Statistics for Managers using Microsoft Excel.
 Catalogue No: BS-338  Credit Hours: 3  Text Book: Advanced Engineering Mathematics by E.Kreyszig  Reference Books  Probability and Statistics by.
© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Chapter 12 Describing Data.
Basic Definitions  Statistics Collect Organize Analyze Summarize Interpret  Information - Data Draw conclusions.
6.1 What is Statistics? Definition: Statistics – science of collecting, analyzing, and interpreting data in such a way that the conclusions can be objectively.
(a.k.a: The statistical bare minimum I should take along from STAT 101)
CHAPTER 1 Basic Statistics Statistics in Engineering
Descriptive Statistics Roger L. Brown, Ph.D. Medical Research Consulting Middleton, WI Online Course #1.
AP Stats Chapter 1 Review. Q1: The midpoint of the data MeanMedianMode.
Exploratory Data Analysis
Chapter 2 Describing Data.
Wednesday, May 13, 2015 Report at 11:30 to Prairieview.
Chapter 21 Basic Statistics.
Describing and Displaying Quantitative data. Summarizing continuous data Displaying continuous data Within-subject variability Presentation.
Determination of Sample Size: A Review of Statistical Theory
7.7 Statistics and Statistical Graphs. Learning Targets  Students should be able to… Use measures of central tendency and measures of dispersion to describe.
BUSINESS STATISTICS I Descriptive Statistics & Data Collection.
MMSI – SATURDAY SESSION with Mr. Flynn. Describing patterns and departures from patterns (20%–30% of exam) Exploratory analysis of data makes use of graphical.
Exam Review Day 6 Chapters 2 and 3 Statistics of One Variable and Statistics of Two Variable.
Review Lecture 51 Tue, Dec 13, Chapter 1 Sections 1.1 – 1.4. Sections 1.1 – 1.4. Be familiar with the language and principles of hypothesis testing.
Chap 18-1 Copyright ©2012 Pearson Education, Inc. publishing as Prentice Hall Chap 18-1 Chapter 18 A Roadmap for Analyzing Data Basic Business Statistics.
Appendix B: Statistical Methods. Statistical Methods: Graphing Data Frequency distribution Histogram Frequency polygon.
The field of statistics deals with the collection,
Business Statistics, 4e, by Ken Black. © 2003 John Wiley & Sons. 3-1 Business Statistics, 4e by Ken Black Chapter 3 Descriptive Statistics.
Descriptive Statistics – Graphic Guidelines
LIS 570 Summarising and presenting data - Univariate analysis.
MODULE 3: DESCRIPTIVE STATISTICS 2/6/2016BUS216: Probability & Statistics for Economics & Business 1.
Homework solution#1 Q1: Suppose you have a sample from Palestine University and the distribution of the sample as: MedicineDentistEngineeringArtsCommerce.
GROUPED DATA LECTURE 5 OF 6 8.DATA DESCRIPTIVE SUBTOPIC
AP PSYCHOLOGY: UNIT I Introductory Psychology: Statistical Analysis The use of mathematics to organize, summarize and interpret numerical data.
Chapter 18 Data Analysis Overview Yandell – Econ 216 Chap 18-1.
Descriptive Statistics ( )
Thursday, May 12, 2016 Report at 11:30 to Prairieview
Exploratory Data Analysis
Statistical Methods Michael J. Watts
MATH-138 Elementary Statistics
Review 1. Describing variables.
Statistical Methods Michael J. Watts
Descriptive measures Capture the main 4 basic Ch.Ch. of the sample distribution: Central tendency Variability (variance) Skewness kurtosis.
BUSINESS MATHEMATICS & STATISTICS.
Support for English, maths and ESOL Module 7: Developing the personal maths skills of teachers and assessors Master class 4: Handling data.
AND.
Descriptive Statistics
Averages and Variation
Description of Data (Summary and Variability measures)
DS1 – Statistics and Society, Data Collection and Sampling
Numerical Descriptive Measures
Basic Statistical Terms
Welcome!.
Lesson 13.1 How do you find the probability of an event?
Review for Exam 1 Ch 1-5 Ch 1-3 Descriptive Statistics
MBA 510 Lecture 2 Spring 2013 Dr. Tonya Balan 4/20/2019.
Higher National Certificate in Engineering
Describing Data Coordinate Algebra.
Introductory Statistics
Presentation transcript:

MATHS CORE AND OPTIONAL ASSESSMENT STANDARDS Found in the Subject Assessment Guidelines (SAG) Dated January 2008

LO4 Core Assessment Standards

GRADE 10 (10.4.1) a) Collect, organise and interpret univariate numerical data in order to determine –Measures of central tendency (mean, median, mode) of grouped and ungrouped data and knows which is the most appropriate under given conditions –Measures of dispersion: range, percentiles, quartiles, interquartile and semi-interquartile range b) Represent data effectively, choosing appropriately from: –Bar and compound bar graphs –Histograms (grouped data) –Frequency polygons –Pie charts –Line and broken line graphs

GRADE 11 (11.4.1) a) Calculate and represent measures of central tendency and dispersion in univariate numerical data by: –Five number summary (maximum, minimum quartiles) –Box and whisker diagrams –Ogives –Calculating the variance and standard deviation sets of data manually (for small sets of data) and using available technology (for larger sets of data) and representing results graphically using histograms and frequency polygons b) Represent bivariate numerical data as a scatter plot and suggest intuitively whether a linear, quadratic or exponential function would best fit the data (problems should include issues related to health, social, economic, cultural, political and environmental issues)

LEARNING OUTCOME 1 Optional: –12.1.3: Correctly interpret the recursive formulae (e.g. T n+1 = T n + T n-1 )

LEARNING OUTCOME 2 –None of the Assessment Standards are optional

LEARNING OUTCOME 3 OPTIONAL ; ; : Euclidian Geometry

LEARNING OUTCOME 4 OPTIONAL (a) : Demonstrate the ability to draw a suitable sample from a population and understand the importance of sample size in predicting the mean and standard deviation of a population (b) : deals with the regression function (c) : deals with the correlation co-efficient

LO4 continued OPTIONAL ; ; : the whole of probability

LO4 continued OPTIONAL ; ; : (a)Identify potential sources of bias, errors in measurement, and potential uses and misuses of statistics and charts and their effects. (A critical analysis of misleading graphs and claims made by persons or groups trying to influence the public is implied here.) (b) Effectively communicate conclusions and predictions that can be made from the analysis of data

LO4 continued OPTIONAL : Differentiate between symmetric and skewed data and make relevant deductions : Identify data which is normally distributed about a mean by investigating appropriate histograms and frequency polygons

LO4 continued ; ; : Use theory learned in this grade in an authentic integrated form of assessment (e.g. in an investigative project) (e.g. in an investigative project)