Inferential Reasoning in Statistics. PPDAC Problem, question, purpose for investigating Plan, Data, Analyse data, Draw a conclusion, justify with evidence.

Slides:



Advertisements
Similar presentations
CHAPTER TWELVE ANALYSING DATA I: QUANTITATIVE DATA ANALYSIS.
Advertisements

Additional Measures of Center and Spread
Understanding and Comparing Distributions
Functional Question (and lesson) Higher (Statistics 2) For the week beginning ….
Making the call Year 10 Some activities to immerse students in ideas about sample, population, sampling variability and how to make a “claim” when comparing.
Analysis. Start with describing the features you see in the data.
Dual Tragedies in the B-ham Paper. Module 2 Simple Descriptive Statistics and Univariate Displays of Data A Tale of Three Cities George Howard, DrPH.
“Teach A Level Maths” Statistics 1
Level 1 Multivariate Unit
Topic 2: Statistical Concepts and Market Returns
PPDAC Cycle.
Understanding and Comparing Distributions
The use of statistics in psychology. statistics Essential Occasionally misleading.
Meet the Kiwis…. Population of kiwis… Codes… Species Region GS-Great Spotted, NIBr-NorthIsland Brown, Tok-Southern Tokoeka NWN-North West Nelson, CW-Central.
Informal statistical inference: Years 10 to 12 Maxine Pfannkuch and Chris Wild The University of Auckland.
Quantitative Skills: Data Analysis
Report Exemplar. Step 1: Purpose State the purpose of your investigation. Pose an appropriate comparison investigative question and do not forget to include.
© Copyright McGraw-Hill CHAPTER 3 Data Description.
The Argument for Using Statistics Weighing the Evidence Statistical Inference: An Overview Applying Statistical Inference: An Example Going Beyond Testing.
Welcome to Common Core High School Mathematics Leadership
Research & Statistics Looking for Conclusions. Statistics Mathematics is used to organize, summarize, and interpret mathematical data 2 types of statistics.
How much do you smoke?. I Notice... That the median for the males is 13.5 cigarettes per day and the median for females is 10 cigarettes per day. This.
Writing the question. PPDAC Problem, question, purpose for investigating Plan, Data, Analyse data, Draw a conclusion, justify with evidence.
1 PUAF 610 TA Session 2. 2 Today Class Review- summary statistics STATA Introduction Reminder: HW this week.
Chapter 21 Basic Statistics.
Biostatistics Class 1 1/25/2000 Introduction Descriptive Statistics.
Is there a difference in how males and female students perceive their weight?
Case Studies A detailed picture of one or a few subjects. Tells us a great story…but is just descriptive research. Does not even give us correlation data.
Agenda Descriptive Statistics Measures of Spread - Variability.
Hotness Activity. Descriptives! Yay! Inferentials Basic info about sample “Simple” statistics.
The use of statistics in psychology. statistics Essential Occasionally misleading.
Carrying out a statistics investigation. A process.
Stage 1 Statistics students from Auckland university Using a sample to make a point estimate.
Revision Analysing data. Measures of central tendency such as the mean and the median can be used to determine the location of the distribution of data.
Statistics Lecture 3. Last class: types of quantitative variable, histograms, measures of center, percentiles and measures of spread…well, we shall.
The field of statistics deals with the collection,
IMPORTANCE OF STATISTICS MR.CHITHRAVEL.V ASST.PROFESSOR ACN.
PPDAC Cycle.
Education 793 Class Notes Inference and Hypothesis Testing Using the Normal Distribution 8 October 2003.
Use statistical methods to make an inference. Michelle Dalrymple.
Concept: Comparing Data. Essential Question: How do we make comparisons between data sets? Vocabulary: Spread, variation Skewed left Skewed right Symmetric.
Statistical Thinking Julia Horring & Pip Arnold TEAM Solutions University of Auckland.
ANNOUCEMENTS 9/3/2015 – NO CLASS 11/3/2015 – LECTURE BY PROF.IR.AYOB KATIMON – 2.30 – 4 PM – DKD 5 13/3/2015 – SUBMISSION OF CHAPTER 1,2 & 3.
Unit 1 - Graphs and Distributions. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data.
KIWI KAPERS Species Weight(kg)Height (cm) Region/Gender.
Introduction Data sets can be compared by examining the differences and similarities between measures of center and spread. The mean and median of a data.
EOM6 ASSESSMENT: THE DATA PROJECT Wake Forest. OVERVIEW  Students will create a statistics project as their End of Module 6 Assessment by collecting.
Multi-variate data internal 4 Credits. achieved The student: Poses an appropriate comparison question, with or without guidance from the teacher,
Data analysis is one of the first steps toward determining whether an observed pattern has validity. Data analysis also helps distinguish among multiple.
Experimental Research
Data Analysis.
Topic 4:Statistics Learning Intention: to solve a statistics problem using the PPDAC enquiry cycle. To classify data as discrete or Continuous. Success.
Data Analysis-Descriptive Statistics
Statistics Collecting and analyzing large amounts of numerical data
Inference.
Box and Whisker Plots.
Inferences to the population
Rethinking Junior Statistics
“Teach A Level Maths” Statistics 1
Using your knowledge to describe the features of graphs
“Teach A Level Maths” Statistics 1
Random Sampling 2/5/19 This lesson continues students’ work with random sampling. The lesson engages students in two activities that investigate random.
No, she only ordered one wheel for each triangle No, she only ordered one wheel for each triangle. She should have order 30 wheels. 3 = #of wheels.
(-4)*(-7)= Agenda Bell Ringer Bell Ringer
Box and Whisker Plots.
Sampling Distributions
Gaining Achieved.
Samples and Populations
Samples and Populations
Samples and Populations
Presentation transcript:

Inferential Reasoning in Statistics

PPDAC Problem, question, purpose for investigating Plan, Data, Analyse data, Draw a conclusion, justify with evidence

When we are just beginning to learn how to reason comparatively we have to keep the principle of statistical inference, the link between sample and population, to the forefront.

We need to be continually reminded that statistical inference requires us to invoke two quite distinct kinds of thoughts. We should have thoughts about the two samples and we should have quite different kinds of thoughts about the two populations from which those samples were drawn.

We must distinguish between these two different ways of thinking and also be able to give a clear indication as to which one is happening. Through language we can clearly signal when we are verbalizing about what we see in the data (descriptive thoughts) and when we are verbalizing about thoughts which involve looking beyond these data to what may be happening back in the populations (inferential thoughts).

The following has been adapted from Telling Data Stories: Essential Dialogues for Comparative Reasoning Maxine Pfannkuch, Matt Regan, and Chris Wild The University of Auckland, New Zealand Nicholas J. Horton Smith College, Northampton, MA, USA

Descriptive thinking: Describe what can be seen in the samples. Inferential thinking: Make inferences about whether the patterns revealed by the samples might persist back in the two populations.

Discussion Investigators analysed the sodium content of some beef (B) hot dogs and some poultry (P) hot dogs. Note: for beef hot dogs n=20, for poultry hot dogs n=17. Discuss in pairs what statements you would make from the box and whisker plots.

What sort of statements did you want to make? – Did you describe what you can see in the samples? – Did you infer about what might be happening back in the two populations? – Did you consider sample sizes? Does it matter?

The investigators made statements from the plots. Decide whether each statement is descriptive or inferential. Note for beef hot dogs n=20, for poultry n=17

Descriptive or inferential The median sodium content for poultry hot dogs is 430 mg, almost 50 mg more than the median sodium content for beef hot dogs. Descriptive: Refers to the sample

Descriptive or inferential The medians indicate that a typical value for the sodium content of poultry hot dogs is greater than a typical value for beef hot dogs.

Descriptive or inferential The medians indicate that a typical value for the sodium content of poultry hot dogs is greater than a typical value for beef hot dogs. Inferential: Refers to the population

Descriptive or inferential The range for the beef hot dogs is 392 mg, versus 231 mg for the poultry hot dogs Descriptive: refers to the sample

Descriptive or inferential The ranges indicate that, overall, there is more spread (variation) in the sodium content of beef hot dogs than poultry hot dogs.

Descriptive or inferential The ranges indicate that, overall, there is more spread (variation) in the sodium content of beef hot dogs than poultry hot dogs. Inferential: refers to the population

Descriptive or inferential The IQRs for sodium content are mg for beef hot dogs and 156 mg for poultry hot dogs. Descriptive: refers to the samples

Descriptive or inferential The IQRs suggest that the spread within the middle half of the data for beef hot dogs is similar to the spread within the middle half of the data for poultry hot dogs.

Descriptive or inferential The IQRs suggest that the spread within the middle half of the data for beef hot dogs is similar to the spread within the middle half of the data for poultry hot dogs. Inferential: refers to the population

Descriptive or inferential The box plots also suggest that each distribution is somewhat skewed right.

Descriptive or inferential The box plots also suggest that each distribution is somewhat skewed right. Inferential: refers to the population

Descriptive or inferential Considering the degree of variation in the data and the amount of overlap in the box plots, a difference of 50 mg between the medians is not really that large.

Descriptive or inferential It is interesting to note that more than 25% of beef hot dogs have less sodium than all poultry hot dogs. On the other hand, the highest sodium levels are for beef hot dogs.

Think about… Is the question about the data collected or is the purpose of the question to make a decision about some wider universe?

If you posed a question such as “Do poultry hot dogs tend to have a higher sodium content level than beef hot dogs?”, on what basis would you make a decision?

Are you aware of concepts such as sample, population, sample distribution, population distribution, sampling variability?