agus (Ih years) of 11 children and the numbers of words in their vocabulary. Complete parts (a) through (d) below. Click here to view the data table, Click here to view the table of critical values for the Pearson correlation coefficient, Data table - X Critical values for the pearson correlation coefficient a) Display the dat O A. Age, x Vocabulary size, y Critical Values for the Pearson Correlation Coefficient 1 6. 3000- 2400- TI 2 210 3 E 1800- 1200 600- . 590 The correlation is significant when the absolute value of is greater than the value in the table. 4 1300 2200 0- 0 2 4 Age (year 9. 2600 a = 0.01 0.990 0.959 0.917 0.875 0.834 0.798 0.765 0.735 0.708 0.684 0.661 0.641 0.623 O G06 a = 0.05 0.950 in 3. 680 4 0.878 0.811 0.754 0.707 0.666 0.632 0.602 0.576 0.553 0.532 0.514 0.497 2100 (b) Calculate the sa 280 6. 7. 4. 1100 8. 6 2300 9. (Round to three de 10 11 (c) Describe the ty 12 13 There is 14 Print Done 15 Interpret the correl 16 Vocabulary size

Based on the tables can you write or describe a summary for each? Thank you. Descriptive statistics of Sample Characteristics, Drug Use and Mental Health Bivariable Analyses Multivariable Analyses In this study we assess lifetime and recent drug use patterns among 261 heterosexually identified 18- to 25-year-olds through brief street intercept surveys conducted in New York City. Marijuana, hallucinogens, powder cocaine, and ecstasy were the most frequently reported drugs for both lifetime and recent use. Findings further suggest significant differences in lifetime use along the lines of gender, race=ethnicity, and school enrollment for various drugs. Males reported using significantly greater numbers of different drugs compared to females, as did those not enrolled in school compared to school enrollees. These data suggest that illicit drug use in emergent adulthood does not develop in a monolithic manner and synergies must be considered in relation to gender, school enrollment, and…

Estimate the most likely degree of correlation for the scatterplot Options: a. 0 b. .85 c. -.90 d. -.05

You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age 65 69 48 37 49 27 62 64 Ho: p = 0 Ha: p = 0 r= Find the p-value p-value= Number of Driver Deaths per 100,000 22 22 34 Find the Linear Correlation Coefficient The p-value is Greater than a Less than (or equal to) a 23 28 20 The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho 33 33 The conclusion is O There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…

Which one of the following summary statistics best matches the data on the abundance of various bird species shown here? Frequency (No. species) 25 20 15 10 5 0 0 Mean = Mean = Mean = 100 200 300 400 500 600 Abundance (No. individuals) 75 individuals, s.d. = 122 individuals 300 individuals, s.d. = 14871 individuals 10 individuals, s.d. = 10 individuals Mean = 10 individuals, s.d. = 14871 individuals Mean 75 individuals, s.d. = 14871 individuals

Find a best fit line for ice cream consumption and murders. This is a classic example of "spurious" correlation. Ice Cream     2,1,2,3,2,4,5,3,2,1,2,1 Murders     8,21,16,18,22,25,22,30,20,10,14,9