Chapter 4: Inductive Arguments This chapter will cover The use of statistical evidence in arguments The reporting of statistical data The use of causal generalizations

Evidence offers strong support ‘beyond a reasonable doubt’ Inductive Reasoning Inductive Reasoning Evidence offers strong support ‘beyond a reasonable doubt’

Inductive Reasoning Likely to be true Evidence is strong support but it is not 100% certain. Evidence gives weight but not certainty.

Inductive Reasoning Using evidence The strength of a conclusion is based on the quality of evidence used to support the conclusion.

Reasoning Inductive Deductive Cycle - bump- misfire Cycle - smooth road - it does not misfire Cycle – 3rd bump-misfire Conclusion? The horn is powered exclusively by electricity from the battery. The battery is dead. Conclusion? Logically conclude that the misfiring is caused by the bumps-induction Logically if the battery is dead the horn will not work-deduction

Inductive Reasoning Induction Drawing generalizations from known facts – research, statistical evidence Finding truth by making observations

Statistical Evidence Why we use statistics Control over the unknown To make predictions and decisions To anticipate accurate information Connect patterns in our lives

Statistical Evidence Data collected by polling and research studies Leads to Statistical Evidence Statistical generalizations Data collected by polling and research studies Gallup poll How people vote Harris poll Inferences from statistical evidence

How Research is Done Three questions What do I want to find out? Characteristic of interest 2. Whom do I want to know about? Target population 3. Whom can I study to get accurate answers? Sample

Sample Members of the target population Must be large enough Must be random Must be representative

Skill Analyze the quality of statistical evidence by noting the size, representation, and randomness of the sample

Sample Reliability Sample size 1,000 randomly selected individuals 2. Representative If not it is biased 3. Significant characteristics Sometimes difficult to know 4. Biased questions Loaded or leading questions

Causal Generalizations Reasons Eliminate difficulties Prevent future problems Human curiosity

Hume’s Method Hume’s Conditions Interpretation 1. X, the cause, preceded y, the effect, in time 2. X and y are contiguous (in contact with one another) in time and place. 3. There is a history of (1) and (2); that is, there is a history of x preceding y and of x and y being related in time and place If one thing causes another, the cause must come before the effect The need for a relationship in time and space between cause and effect Chart a tendency

Hume’s conditions Considerations “Correlation is not causation.” A “third-variable” could be the source of the relationship.

Cause and Effect Technical Causation Necessary condition- condition must be present if the effect is present Sufficient condition- if condition is present, effect will definitely occur

Stop and Think It has been said that holding elections is a necessary but not a sufficient condition for establishing a democracy. What do you believe would be other necessary factors that would become sufficient for establishing a democratic government?

Mill’s Analysis John Stuart Mill Canons Foundational to controlled studies

Mill’s Analysis Method of Agreement Method of Difference X is the only factor always present when Y occurs: Therefore, X causes Y The only difference between (Y) happening or not is whether one element (X ) is present If: X is present then Y occurs X is not present then Y does not occur

Chapter 4: Inductive Arguments Checkup Uses of statistical generalizations Multiple causes of a problem Problems with statistical evidence Sample, target audience, characteristic of interest Cause and effect- Hume and Mill’s