Date Period Find the mode, median, mean, lower quartile, upper quartile, interquartile range, and population standard deviation for each data set.

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Algebra 2 ^ L2U0\1^6K EKVujtJaB us`ocfetawka]rge` FLYLCCk.B t iarlclv rrhipgohrtvsx qrbeyswedrdvpezdb. Statistics Notes Name Date Period Find the mode, median, mean, lower quartile, upper quartile, interquartile range, and population standard deviation for each data set. 1) Hits in a Round of Hacky Sack 2) 12 3 8 2 6 4 3 13 5 5 7 7 6 7 4 6 4 4 6 7 7 Games per World Series 3) Games per World Series 4) 4 5 6 7 Games Single Family Home Prices Stem Leaf 27 6 28 8 29 0 2 3 3 3 5 30 7 31 1 2 Key: 29 2 = 292,000 5) # Words Length of Book Titles 6) 4 3 2 1 Shoe Size Size Frequency 7 2 7.5 2 8 2 9 4 10 1 1 2 3 4 5 6 7 8 9 Book d M2w0T1[6Z FKdugtvac qssogfvtcwlayreex HLcLlCL.E h TAslClf QrviDgFhztAsd Erfe]sCeQrsvzewdk.M c VMfaxd[es Cwyixt\hR zi\ndfbinn_iftpeq ZAzlQgZepbbrjaJ m1x. -1-

Draw a dot plot for each data set. 7) 7 3 9 7 2 5 5 5 7 Goals in a Hockey Game 8) Sales Tax State Percent State Percent Maine 6 Maryland 6 Wisconsin 5 Georgia 4 Missouri 4 Nebraska 6 Texas 6 Delaware 0 Alabama 4 Draw a histogram for each data set. 9) Melting Point 10) Substance C Substance C Potassium 63.4 Lead 327.5 Uranium 1,132 Silicon 1,414 Water 0 Copper 1,085 Gold 1,064 Iron 1,538 Sulphuric Acid 10.3 Hours Slept 5 4.5 7.75 8.5 7 7 7 5.25 7.75 6.75 Draw a box-and-whisker plot for each data set. 11) Car Weights (kg) 12) 1,720 1,410 995 1,455 1,160 1,500 1,715 1,340 1,670 1,315 1,965 Melting Point Substance C Substance C Radium 699.8 Plutonium 639.4 Sulphur 115.2 Argon 189.2 Nickel 1,455 Iron 1,538 Gold 1,064 Magnesium 650 Carbon 3,550 Platinum 1,768 e Y2\0Q1J6H DKsuftUaz ASJoxflt\wXaqrCe[ FLNLhCF.v P kablmlu ^r_iagihjt_ss _rxezspemrmv]e_dt.g g JMfakd`eI MwdiQtAh^ JICnnftiOnOiqtEee oaalmgzecbzroab i1s. -2-

13) The height and weight of several adults were recorded: Height (ft) Weight (lbs) 4.55 93.6 4.9 107 5.3 124 5.7 146 6.15 171 6.3 171 It was discovered that this can be modeled by the equation y = 46.9x - 122 where x is height in feet and y is weight in pounds. Weight (pounds) 180 160 140 120 100 4.5 5 5.5 6 6.5 7 Height (feet) a) What does the slope of the line represent? b) What does the y-intercept of this function represent? c) Using this model, what would be the weight of someone who is 5.2 ft tall? Round your answer to the nearest tenth. d) According to the model, what would be the weight of someone who is 6 ft tall? Round your answer to the nearest tenth. e) What height corresponds to a weight of 150 pounds? Round your answer to the nearest hundredth. F C2R0P1E6s xkfumtcaw zsiorfrtnwyairfew xlqlpcv.i W qadlblc er_ilgghttcse trgefsme]rivlecdo.m C ^M`akdxet ZwqiitThy ziinqfdivngintkec VAClzgWeMbzrnaX X1j. -3-

14) The number of times that a school has won the national college basketball tournament is related to the number of times that the school has participated in the tournament. Here is the data for several schools: This relationship can be modeled by y = 0.00669x 2-0.172x + 0.681 where x is the number of appearances in the tournament and y is the number of championships they have won. Appearances Championships Won 3 0 14 0 22 0 26 1 41 4 47 8 Championships Won 8 7 6 5 4 3 2 1 10 20 30 40 50 Appearances a) What does the y-intercept of this function represent? b) According to the model, you would expect a school with 9 appearances to have won how many championships? Round your answer to the nearest whole number. c) Using this model, a school with 56 appearances in the tournament would be expected to have won how many championships? Round your answer to the nearest whole number. d) Based on this model, how many tournament appearances would you expect from a school that won 3 championships? Round your answer to the nearest whole number. j k2q0_1o6q XK_ugtCaw VShoufzt`wPawrgea WLbL[Cl.I _ japlylz vrlikg\h_tpsm OrWeksUeBrWvAeKde.w k BMfamdUeM \wkiqtehd jiin\fdihnqi\tnev dablbgaexbdrhak Q1]. -4-

15) The National Oceanic and Atmospheric Administration tracks the amount of oysters harvested from the Chesapeake Bay each year: Years since 1900 Oysters (metric tons) 3 48.9 14 29.8 27 22.5 64 6.36 79 2.78 90 2.35 This can be modeled by the equation y = 53.9 0.965 x where x is the number of years since 1900 and y is the amount of oysters harvested in metric tons. Oysters (metric tons) 40 30 20 10 20 40 60 80 Years since 1900 a) What does the y-intercept of this function represent? b) Using this model, how many metric tons of oysters were harvested in 1953? Round your answer to the nearest tenth. c) According to the model, how many metric tons oysters were harvested in 1865? Round your answer to the nearest tenth. d) The model indicates that 12 metric tons of oysters were harvested in what year? Round your answer to the nearest year. W Q2g0D1e6X UKRupt]aR SSeo_fmtuw^aCr[ej xlnlacx.\ C wavl]lk Nrzi^gEhEtXsM vrfegsvemrlvmefdv.z O IMvahdleU LwFiBtph_ tisncfliknji_tgem mavlmgledblrxaz m1z. -5-

16) Economists have found that the amount of corruption in a country is correlated to the productivity of that country. Productivity is measured by gross domestic product (GDP) per capita. Corruption is measured on a scale from 0 to 100 with 0 being highly corrupt and 100 being least corrupt: Corruption Score GDP Per Capita ($) 18 2,860 25 5,230 37 10,600 53 15,800 58 18,500 64 25,800 This can be modeled by the equation y = 1610 1.04 x where x is the corruption score and y is GDP per capita in dollars. GDP Per Capita ($) 25000 20000 15000 10000 5000 10 20 30 40 50 60 Corruption Score a) What does the y-intercept of this function represent? b) According to the model, what would be the GDP per capita of a country with a corruption score of 31? Round your answer to the nearest dollar. c) Using this model, a country with a corruption score of 98 would have what GDP per capita? Round your answer to the nearest dollar. d) A GDP per capita of $9,800 corresponds to what corruption score, according to the model? Round your answer to the nearest whole number. b e2g0i1q6o RKbuAtnaT dsnotfutqwwa_rweg bldlmcg.t u gaplclt vrxi]gxhktosk HrlefsgexrBvCewdV.[ f omvawdheo NwhiStIhe fipnffaiqngi\thei TAIlSgTeGbkrSaD Y1v. -6-

Algebra 2 s U2_0b1C6u mkauntdak tsto_f`txwiajrlev \LBL[Ct.y N _AblclE drdieg]hftes\ vrmesskeurfvyerd`. Statistics Notes Name Date Period Find the mode, median, mean, lower quartile, upper quartile, interquartile range, and population standard deviation for each data set. 1) Hits in a Round of Hacky Sack 2) Games per World Series 12 3 8 2 6 4 3 13 7 7 6 7 4 6 4 4 5 5 6 7 7 Mode = 3 and 5, Median = 5, Mean = 6.1, Q 1 = 3, Q 3 = 8, IQR = 5 and s = 3.59 Mode = 7, Median = 6, Mean = 5.91, Q 1 = 4, Q 3 = 7, IQR = 3 and s = 1.24 3) 5) Games per World Series # Words 4 5 6 7 Games Mode = 6, Median = 6, Mean = 5.73, Q 1 = 5, Q 3 = 6, IQR = 1 and s = 0.86 Length of Book Titles 4 3 2 1 1 2 3 4 5 6 7 8 9 Book Mode = 2, Median = 2, Mean = 2.33, Q 1 = 1.5, Q 3 = 3.5, IQR = 2 and s = 1.05 4) 6) Single Family Home Prices Stem 27 6 28 8 Leaf 29 0 2 3 3 3 5 30 7 31 1 2 Key: 29 2 = 292,000 Mode = 293,000, Median = 293,000, Mean = 295,454.55, Q 1 = 290,000, Q 3 = 307,000, IQR = 17,000 and s = 10,192.36 Shoe Size Size Frequency 7 2 7.5 2 8 2 9 4 10 1 Mode = 9, Median = 8, Mean = 8.27, Q 1 = 7.5, Q 3 = 9, IQR = 1.5 and s = 0.94 R x2j0f1s6x _KVu[tfaS msbojfmtgwgatrdeq OLCL^CI.Z F MAhlclg KrxiAgPhJtYs^ XrYeosCe^rJveekdM.M m LMOaudIeN hwxirtahj qidnsfzibnzihtyef BAklggKeubNrAaI W1P. -1-

Draw a dot plot for each data set. 7) Goals in a Hockey Game 8) Sales Tax 7 3 9 7 2 5 5 5 State Percent State Percent 7 Maine 6 Maryland 6 Wisconsin 5 Georgia 4 Missouri 4 Nebraska 6 Texas 6 Delaware 0 2 3 4 5 6 7 8 9 Alabama 4 0 1 2 3 4 5 6 Draw a histogram for each data set. 9) Melting Point 10) Hours Slept Substance C Substance C 5 4.5 7.75 8.5 7 7 Potassium 63.4 Lead 327.5 7 5.25 7.75 6.75 Uranium 1,132 Silicon 1,414 Water 0 Copper 1,085 Gold 1,064 Iron 1,538 Sulphuric Acid 10.3 5 4 3 2 3 1 2 4 5 6 7 8 9 1 0 200 400 600 800 1,000 1,200 1,400 1,600 Draw a box-and-whisker plot for each data set. 11) Car Weights (kg) 12) Melting Point 1,720 1,410 995 1,455 1,160 Substance C Substance C 1,500 1,715 1,340 1,670 1,315 Radium 699.8 Plutonium 639.4 1,965 Sulphur 115.2 Argon 189.2 Nickel 1,455 Iron 1,538 Gold 1,064 Magnesium 650 1000 1200 1400 1600 1800 Carbon 3,550 Platinum 1,768 1000 2000 3000 g v2v0i1i6l wklultmax ISHoIf\tawya[rkeO KLbLHCc.z r FAaldlQ prkigg^hit`sr hrredsteoruvmeddp.h k GMjahdOev EwSiHthhK yi]nvfdihnai`tte] EAEl[gReibwrjaS x1]. -2-

13) The height and weight of several adults were recorded: Height (ft) Weight (lbs) 4.55 93.6 4.9 107 5.3 124 5.7 146 6.15 171 6.3 171 It was discovered that this can be modeled by the equation y = 46.9x - 122 where x is height in feet and y is weight in pounds. Weight (pounds) 180 160 140 120 100 4.5 5 5.5 6 6.5 7 Height (feet) a) What does the slope of the line represent? The number of pounds heavier an adult one foot taller would weigh b) What does the y-intercept of this function represent? The weight of an adult zero feet tall c) Using this model, what would be the weight of someone who is 5.2 ft tall? Round your answer to the nearest tenth. 121.9 lbs d) According to the model, what would be the weight of someone who is 6 ft tall? Round your answer to the nearest tenth. 159.4 lbs e) What height corresponds to a weight of 150 pounds? Round your answer to the nearest hundredth. 5.8 ft q z2^0l1w6q UKGuItJaX rsroafjtpwsaerqek JLrLKC[.W Y maclwlp qrmiagdhrtdsn gr`eysqebrzviepdx.i _ BM^aidWeT ^wyiztfhz GISnSfpibnvi[tHeU ZA^lJgweUbQrOaE I1k. -3-

14) The number of times that a school has won the national college basketball tournament is related to the number of times that the school has participated in the tournament. Here is the data for several schools: This relationship can be modeled by y = 0.00669x 2-0.172x + 0.681 where x is the number of appearances in the tournament and y is the number of championships they have won. Appearances Championships Won 3 0 14 0 22 0 26 1 41 4 47 8 Championships Won 8 7 6 5 4 3 2 1 10 20 30 40 50 Appearances a) What does the y-intercept of this function represent? The number of championships won by a school with zero tournament appearances b) According to the model, you would expect a school with 9 appearances to have won how many championships? Round your answer to the nearest whole number. 0 championships c) Using this model, a school with 56 appearances in the tournament would be expected to have won how many championships? Round your answer to the nearest whole number. 12 championships d) Based on this model, how many tournament appearances would you expect from a school that won 3 championships? Round your answer to the nearest whole number. 35 appearances V ]2s0Z1O6P QKWuxt`aM fseopfvtbwxafrhek [LZLCCg.X u _AYlgl^ ar[i\guhmtosr LrOeCsweYrMv]e^d`.D Z tmcawdget FwPiZtUhv VIWnzfqiHn`iFthev RA^lNgGeEbcrGaj _1x. -4-

15) The National Oceanic and Atmospheric Administration tracks the amount of oysters harvested from the Chesapeake Bay each year: This can be modeled by the equation y = 53.9 0.965 x where x is the number of years since 1900 and y is the amount of oysters harvested in metric tons. Years since 1900 Oysters (metric tons) 3 48.9 14 29.8 27 22.5 64 6.36 79 2.78 90 2.35 Oysters (metric tons) 40 30 20 10 20 40 60 80 Years since 1900 a) What does the y-intercept of this function represent? The amount of oysters harvested in 1900 b) Using this model, how many metric tons of oysters were harvested in 1953? Round your answer to the nearest tenth. 8.2 metric tons c) According to the model, how many metric tons oysters were harvested in 1865? Round your answer to the nearest tenth. 187.6 metric tons d) The model indicates that 12 metric tons of oysters were harvested in what year? Round your answer to the nearest year. 1942 i v2]0j1d6[ jkmuwtwaa NS_oSfQtSwKa`rDeW ^LtL[C[.t m HALlmlQ BrqiKgmhItasx VreepsGexrev\eadP.^ \ YMbawdqeX `wmi_tohe ji[nofhiinsijtueu KAQlugBeDbkrQaD t1u. -5-

16) Economists have found that the amount of corruption in a country is correlated to the productivity of that country. Productivity is measured by gross domestic product (GDP) per capita. Corruption is measured on a scale from 0 to 100 with 0 being highly corrupt and 100 being least corrupt: Corruption Score GDP Per Capita ($) 18 2,860 25 5,230 37 10,600 53 15,800 58 18,500 64 25,800 This can be modeled by the equation y = 1610 1.04 x where x is the corruption score and y is GDP per capita in dollars. GDP Per Capita ($) 25000 20000 15000 10000 5000 10 20 30 40 50 60 Corruption Score a) What does the y-intercept of this function represent? The GDP per capita of a country with a corruption score of zero b) According to the model, what would be the GDP per capita of a country with a corruption score of 31? Round your answer to the nearest dollar. $5,431 c) Using this model, a country with a corruption score of 98 would have what GDP per capita? Round your answer to the nearest dollar. $75,178 d) A GDP per capita of $9,800 corresponds to what corruption score, according to the model? Round your answer to the nearest whole number. 46 e B2y0z1E6A FKYuptxas FSAoSfNthwza`rUea glvlrcl.m z waulnlr `rhi[gdhotesq CrMensOe[r[vse_dO.m H DMHandleT `wgietmha SIhn]fgiknJiMtVeW YAmlgg\exbrrtaw c1e. -6-