Question 4 You want to obtain a sample to estimate a population mean age of the incoming fall term transfer students. Based on previous evidence, you believe the population standard deviation is approximately \( \sigma=7 \). You would like to be \( 95 \% \) confident that your estimate is within 1.6 of the true population mean. How large of a sample size is required? Do not round between steps. Use technology to find z-score. Give your answer in whole people. Make sure you use the correct rounding rule for samples size. , Next Questions

Which of the followring statements are TRUE about the Hormal Distribution? Check all that apply. \( \square \) The distribution is symmetric with a single peak. \( \square \) about \( 95 \% \) of all data values lie within 1 standard deviation of the mean. \( \square \) The graph of the Hormal Distribution is bell-shaped, with tapering tails that never actually touch the horizontal axis. \( \square \) Data values farther from the mean are less common than data values closer to the mean. \( \square 50 \% \) of the data values lie at or above the mean. Data values are spread evenly around the mean. The mean, median and mode are all equal and occur at the center of the distribution.

EJERCICIO 7 -1 Se muestran las tallas de calzado de los últimos 20 clientes que han entrado a una zapatería \[ \begin{array}{l}25,22.5,26,26.5,27,25,23,24,24,23,24,24.5,24.5,24,23.5,24.5 \\ 23.5,24.5,25,23.5\end{array} \] Ordena las tallas y elabora una gráfica de columnas para representar los datos

In a class of 40 leamers, 32 take Mathematics, 23 History and 4 do not take Mathematics or History. Draw a Venn diagram to illustrate the given information. How many learners take Mathematics and History Determine the Following: the probability that a learner takes History and Mathernatics. the probability that a learner does not take Mathematics. How many learners take History but not Mathematics?

In a normal distribution, a data value located 1.2 standard deviations below the mean has Standard Score: \( \mathrm{z}=\square \) In a normal distribution, a data value located 2.4 standard deviations above the mean has Standard Score: \( \mathrm{z}=\square \) In a normal distribution, the mean has Standard Score: \( \mathrm{z}=\square \)

Consider the Standard Normal distribution. The mean is always \( \square \) and the standard deviation is always