If, in a simple random sample of voters, the sample-mean income is $45,000, the sample size is 1600, thesample standard-deviation is $4,000, what is the standard error of the sample mean? give a(n approximate)95% confidence interval for the population mean.

Refer to the payoff matrix. suppose that speedy bike and power bike are the only two bicycle manufacturing firms serving the market. both can choose large or small advertising budgets. is there a nash equilibrium solution to this game?

An insurance company estimates the probability of an earthquake in the next year to be 0.0015. the average damage done to a house by an earthquake it estimates to be $90,000. if the company offers earthquake insurance for $150, what is company`s expected value of the policy? hint: think, is it profitable for the insurance company or not? will they gain (positive expected value) or lose (negative expected value)? if the expected value is negative, remember to show "-" sign. no "+" sign needed for the positive expected value

Reliability and validity reliability and validity are two important considerations that must be made with any type of data collection. reliability refers to the ability to consistently produce a given result. in the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways. unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. to illustrate this concept, consider a kitchen scale that would be used to measure the weight of cereal that you eat in the morning. if the scale is not properly calibrated, it may consistently under- or overestimate the amount of cereal that’s being measured. while the scale is highly reliable in producing consistent results (e.g., the same amount of cereal poured onto the scale produces the same reading each time), those results are incorrect. this is where validity comes into play. validity refers to the extent to which a given instrument or tool accurately measures what it’s supposed to measure. while any valid measure is by necessity reliable, the reverse is not necessarily true. researchers strive to use instruments that are both highly reliable and valid.