Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. x days 76 79 36 95 207 y km/100 14.2 19.6 5.4 11.2 35.9 (a) Verify that Σx = 493, Σy = 86.3, Σx2 = 65,187, Σy2 = 2029.21, Σxy = 11317.3, and r ≈ 0.93885. Σx   Σy   Σx2   Σy2   Σxy   r   (b) Use a 1% level of significance to test the claim ρ > 0. (Use 2 decimal places.) t   critical t   (c) Verify that Se ≈ 4.6183, a ≈ 0.5575, and b ≈ 0.1694. Se   a   b    Find the predicted distance (km/100) when a drift bottle has been floating for 60 days. (Use 2 decimal places.) km/100

The numbers of polio cases in the world are shown in the table for various years. Year Number of Polio Cases (thousands) 1988 1992 1996 2000 2005 2007 350 138 36 5 3.2 1.3 Let f(t) be the number of polio cases (in thousands) t years after 1980. Copy the data to Desmos to draw a scatterplot of the data. Make sure to adjust the years so they represent years after 1980. a) Is it better to model the data with a linear or with an exponential model? [Select an answer b) Use regression in Desmos to find an appropriate model for f. Make sure to check Log mode in the parameter window in Desmos if you are fitting an exponential model. f(t) Round the coefficients to 4 decimal places. Hint: Use the variable t from the drop down menu when entering the equation. Do not just type in t. c) Predict the number of polio cases in 2014. d) Find the approximate half-life of the number of polio cases. Round the answer to one decimal place. years

Can you please use this data to determine the power at a wind speed of 14 m/s using linear spline interpolation.

Construct a scatter diagram using the data table to the right. This data is from a study comparing the amount of tar and carbon monoxide (CO) in cigarettes. Use tar for the horizontal scale and use carbon monoxide (CO) for the vertical scale. Determine whether there appears to be a relationship between cigarette tar and CO. Full data set D CO 15 10 со Tar 10 Tar Tar CO 16 10 2 3 9. 8 11 15 16 15 18 10 1 1 14 7 12 11 18 17 16 7 11 9. Construct a scatter diagram. ОА. В. С. ACO 20- 16 125 ACO 20- ACO 20- 163 123 83 4= ACO 20- 163 125 8- 165 125 85 8= 4= 45 Tar E 4- Tar Tar Tar 0 0 4 8 12 16 20 0- 0- 0 4 8 12 16 20 0 4 8 12 16 20 Ó 4 8 12 16 20 Is there a relationship between cigarette tar and CO? A. Yes, as the amount of tar increases the amount of carbon monoxide decreases. B. Yes, as the amount of tar increases the amount of carbon monoxide also increases. C. No, there appears to be no relationship. 出

Construct a scatter diagram using the data table to the right. This data is from a study comparing the amount of tar and carbon monoxide (CO) in cigarettes. Use tar for the horizontal scale and use carbon monoxide (CO) for the vertical scale. Determine whether there appears to be a relationship between cigarette tar and CO. Full data setO CO CO 13 Tar Tar Tar CO 16 14 2 14 8. 11 12 11 14 18 10 15 7 18 7| 17 18 16 17 9. 17 18 Construct a scatter diagram. O A. OB. Oc. D. ACO 20- 16 12- ACO 20- 165 12 8 4. ACO 20 164 123 84 ACO 20- 16 125 8 4. 8- 4. Tar Tar Tar Tar 04 048 121620 048 1216 20 0 48 121620 0 4 8 121620 551

ở 36% O CLWK CH 5C & 5D.pdf IB MAI SL HONORS Seniors Date Block 1) Fifteen studénts were weighed and their pulse rates were measured: Weight (x kg) 46 37 32 57 47 64 42 30 52 56 65 43 36 28 40 Pulse rate (y beats per mín) 65 59 54 74 69 87 61 59 70 69 75 60 56 53 58 a Draw a scatter diagram for the data. b Calculate r. c Describe the relationship between weight and pulse rate. d Calculate the mean point (T, T). e Locate the mean point on the scatter diagram, then use it in drawing a line of best fit. f Estimate the pulse rate of a 50 kg student. Comment on the reliability of your estimate. endar 12 T To Do 116 M Inbox Notifications

IS YOUR DATA BASELINE DATA AUTOCORRELATED. behavior 2 4 6 8 10 o D 2 4 A time ° 6 8 0

The numbers of polio cases in the world are shown in the table for various years. Year Number of Polio Cases (thousands) 1988 1992 1996 2000 2005 2007 350 138 32 6 3.2 1.3 Let f(t) be the number of polio cases (in thousands) t years after 1980. Copy the data to Desmos to draw a scatterplot of the data. Make sure to adjust the years so they represent years after 1980. a) Is it better to model the data with a linear or with an exponential model? Select an answer b) Use regression in Desmos to find an appropriate model for f. Make sure to check Log mode in the parameter window in Desmos if you are fitting an exponential model. f(t) places. Round the coefficients to 4 decimal Hint: Use the variable t from the drop down menu when entering the equation. Do not just type in t. c) Predict the number of polio cases in 2019. d) Find the approximate half-life of the number of polio cases. Round the answer to one decimal place. years

Pls show work so I can understand

Researchers often rely on surveys to capture a subjective assessment of well-being. One study finds that holding everything else constant, people seem to be least happy when they are in their 40's. Another study suggests that money does buy happiness, but its effects diminishes as income rises above $75000 a year. The accompanying data file includes survey daa of 100 working adults' self-assessed happiness on a scale of ) to 100, along with their age and annual income. Estimate and interpret a regression model based on Age, Age 2 and income. Predict happiness with income equal = to $80000 and age equal to 30, 45, and 60 Years Predict happiness with Age equal = to 60  and income equal to 25,000, 75000, and 125000   Happiness Age Income 69 49 52000 83 47 123000 86 72 112000 73 52 166000 89 68 90000 81 37 152000 75 48 58000 56 48 50000 75 56 93000 57 51 27000 77 60 173000 83 55 173000 85 75 68000 82 69 157000 63 39 40000 70 66 107000 78 34 109000 53…