Think of the last time you had a misunderstanding while speaking with someone of the opposite sex. Based on what you have learne
d about gender differences in communication, use specific examples to describe what you think was the root cause of the misunderstanding. Also, explain what approach you might take in the future should a similar situation arise again. << Read Less
This happened to me today. My mother and I got in an argument with someone of the opposite sex this morning. There can be many reasons as to why this happens, but one of the mian root causes are usually things like femminism and masculism. (However, this is not why we were arguing). The man yelled at us and accused us of speaking rudely with an employee at a company.
Now, I've seen things about femminism and masculism on the internet and a "battle between the sexes". The conversations usually heat up when people talk about how the sexes are treated differently or how one has an advantage over the other.
<h3><u><em>Perhaps the most common goal in statistics is to answer the question: Is the variable X (or more likely, X 1 , ... , X p ) associated with a variable Y, and, if so, what is the relationship and can we use it to predict Y?
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<h3><em>Nowhere is the nexus between statistics and data science stronger than in the realm of prediction—specifically the prediction of an outcome (target) variable based on the values of other “predictor” variables. Another important connection is in the area of anomaly detection, where regression diagnostics originally intended for data analysis and improving the regression model can be used to detect unusual records. The antecedents of correlation and linear regression date back over a century.</em></h3>
