PHI 103 week 3 guided responses

I need help responding to the three listed in highlighted
Examples of Inductive Inference 2/20/2017 12:22:33 PM
We have learned in Chapter 5 of our book that inductive inference is the most common kind of inference of all. It happens every day in each of our lives. This discussion will give each student a chance to create examples of common forms of inductive inference.
Prepare: To prepare to answer this prompt take another look at Chapter 5 of our book paying close attention to the names of the various forms of inductive inference. Take a look as well at the required resources from this week.
Reflect: Think about examples you have seen of each type of inductive inference in daily life. Consider the relative strength of such inferences in light of the methods of evaluation that you learned in the chapter.
Write: To answer the prompt create or find one example each of three different types of inductive inference that we learned in Chapter 5. Clearly indicate as well which type of inductive inference it is. For each of your arguments include an analysis of its degree of strength using the evaluative methods we learned in the chapter for that type of argument.
Guided Response: Respond to at least three of your classmates posts. In each case provide substantive thoughts about the strength of the inference. Mention as well what premises you think could be added to strengthen the inference or which might weaken it. How do you think that the argument could be improved?
Discussion 2 – week 3 Leslie Dayson Email this Author 2/21/2017 8:07:32 PM
Casual inference suggests there is a reason to the conclusion that is likely to be or something is a connection based on the conditions of the occurrence of an effect. For instance someone may have heard a piano playing thus one would infer someone is or was playing when in fact it may have been an electronic synthesizer. The original conclusion may have been likely but there are other scenarios that could present the same factor. The elements of correlation of two factors could indicate a causal relationship between them but additional factors should be confirmed to create the actual aspects of a causal relationship (Deak 2012).
Statistical Argument is a direct inference or a non-deductive syllogism. Michael Jordan was the best NBA player in his era. His statistics proves that he was the best NBA player while on the Chicago Bulls team. A position that in principle is generally but not universally true or false is considered a statistical syllogism. All women love rose and chocolates. Southerners drink tea and retirees move to Florida.
Prediction a past sample offers a developing future direction. The assessment seeks to determine the truth it reveals the prediction premise could be accurate and stronger in inferences. For example if one car company has a lost in revenue due to low sales then its likely that other car companies are having the same impact.
Discussion 2 Alyssa Rasmussen Email this Author 2/23/2017 5:38:00 AM
The top three types of inductive inference I am going to write about in this discussion are Arguments of Authority Casual Arguments and Statistical Arguments.
Arguments of Authority: This type of argument is structured in strength due to its authorative voice. An example of this would be if a mother tells her child that they have to separate their dirty clothes by color before they get washed. The child will probably listen because it is his mother who is arguing this claim. To evaluate the strength of this argument I would identify the argument as being an inductive argument of authority. I would also try to evaluate the strength of this argument and look at the weaknesses.
Casual Arguments: Casual Arguments are arguments that are usually presented to us in almost everyday scenarios. We may infer something is true when it turns out not to be. An example of this would be telling your husband a grocery store is open until 10pm on week days and then your husband goes to the grocery store at 9pm on a Monday night and it’s closed because you forgot it was Martin Luther King day.
Statistical Arguments: Statistical Arguments are arguments based on statistics. These arguments could infer that something may statistically be more probable yet still not be correct. An example of this would be Californias earthquake statiistics. Statistics have alarmed scientists to believe that California would have a massive earthqauke in October of 2016 however this massive earthqauke obviously did not occur
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Inductive Reasoning Discussion #2 Denise Winston Email this Author 2/23/2017 2:37:23 PM
The three Inductive Inferences I chose are: Causal Arguments Statistical Arguments and Arguments from Authority:
Causal arguments are based on cause-and-effect and things that happen in everyday occurrences one example is Krispie Kreme has the best donuts.
Statistical arguments are basically statistics and the conclusions come from percentages one example is:
90% of humans are right handed
Pat is Human
Therefore Pat is righthanded
Arguments from authority is a type of argument that is structured in strength due to its authoritative voice it is an inductive argument which one infers that a claim is true because someone say so. An example: Children need a education Therefore Children are expected to go to school everyday.
Reference:
Hardy J. Foster C. &Zuniga Y Postigo G. (2015). With Good Reason: A Guide to Critical Thinking [Electronic version]. Retrieved from http:// content. ashford.edu/