you will be answering to seperate discussion post. i will but one short paragrap

you will be answering to seperate discussion post. i will but one short paragraph each. keep it short and to the point.
1. Lori McEndree
Week 4 Discussion: Generalization
Making an Inference about a Target Group
To make an inference about a target group based on a sample, the sample must be representative of a group that is much larger, chosen at random, and not biased (Sherry & Zhang, 2015). By using a group that is representative of the general population we will get a more accurate result (Sherry & Zhang, 2015). An inference will be true if the information that was provided was true (Sherry & Zhang, 2015).
Sample Size/Random Sample
The reason that a sample must be large enough and chosen at random is that it must be able to represent a group of people stemming from different ages, political views, rural area, and urban areas for example to make an accurate inference (Sherry & Zhang, 2015). If the sample is not large enough or chosen at random there will be an increased risk for bias and error (Sherry & Zhang, 2015).
Inductive Probability/Generalization
Inductive reasoning can be made using conjectures which occur when something that’s stated is believed to be true with no proof (Sherry & Zhang, 2015). The inductive reasoning is based on believing that a pattern that has occurred will continue to be true (Sherry & Zhang, 2015). Inductive probability is used when an attempt is made to give the odds of a future event by looking at the inductive reasoning (Sherry & Zhang, 2015). Inductive probability is used in generalization when an observation is made based on a sample to develop new theories and the probability that they are true.
2. LaChasta Betton
Week 4 Discussion: Generalization
How can we make an inference about a target group based on a sample?
To make an inference about a target group is probability-based sampling that allows a design-based inference about the target sample. When using a large sample size it is more representative of the sample size. A good well-chosen sample will provide most of the information about the particular example parameter.
Why is it necessary that the sample size is large enough, and that the sample is random?
If you pick a small sample size you run a greater risk of the small sample being unusual. A large sample size is beneficial which is more closely approximate to the same size.
Discuss inductive probability. What does it mean and what role does it play in generalization?
In inductive probability will attempt to give the probability of future events based on the past events. Inductive probability is the basis of mathematical basis for learning the perception of pattern.