Inductive reasoning is about making generalized conclusions based on specific observations. For example, if 95% of the apples you pick from your tree are red, you might think that all the apples on your tree are red. This is an example of an inductive generalization. These are generalizations that can be very strong if they are based on a large and representative sample, but they can also be very weak if the sample is too small or biased.Statistical arguments use data and numbers to support a conclusion, but they need to be evaluated carefully bad data or an incorrect interpretation can lead to a false conclusion. Using an analogous argument means that you compare two things, show them to be similar, and suggest that one is true for the other. This can be quite powerful if there are lots of relevant and significant similarities between the two things.
When we make argumentsg, remember that it is also important to use sources that are credible that is, current, accurate, and written by experts. We should also remember to write a clear thesis statement, organize our ideas logically and with proper transitions, support our claims with evidence, and decide how each piece of evidence we provide will strengthen your argument.