3. Take a sample of n = 30 or more (not more than 100) from your identified population and create a table recording the results . Include the table below (enter the individual responses 4. Identify and explain at least one type of bias that could be present in your research 5. Using technology, create a bar chart for your qualitative variable. Be sure to include all appropriate labels in your bar chart . Include a screen clip of your bar chart here . (Hint : Consider using the Describing and Exploring Categorial Data ShinyApp https ://dcmathpathways .shinyapps .io/EDA_categorical 6. What is the sample proportion ? Use appropriate notation . (Example : 30 ~0.7333 of sampled U.S. adults use Facebook ). Make sure that your sample proportion is different from your population proportion 7. Using 1-2 sentences , compare the sample proportion to your identified population proportion (Hint : Consider Similarities , differences , surprises ?) 8. Using the identified population proportion , and The Central Limit Theorem for Proportions manually calculate the mean and the standard error (i.e., the standard deviation of the sampling distribution ) for the sampling proportion for the various sample sizes given below Reminder : According to the Central Limit for Proportions , H=P and o pq where q = 1 - p. n n= 30 n = 120 n= 480 What do you notice happens to the standard error as the sample size increases from 30 to 120, and from 120 to 480 ? (Hint : Does the standard error change in a pattern ? Make at least two observations