nstructions: Please run your analysis using Microsoft Excel data analysis tools. The lab book (yellow book) provides more information about survey reporting. Chapter 15 can provide examples of how you can present your survey results in Excel . Finally, make sure to include a paragraph or two about what you can conclude from your analysis. Please see attache below of "Copy of Sample milestone 4" to get an idea of the deliverable.
M4 Data Analysis Results: Automobile Insurance Preimun & Household income A. Descriptive Statistics 1. Categorical Variable: Gender (D1) i. & ii. Frequency Distribution and Percentages ClassFreq% Male2351 Female2147 Did not answer12 Total45100 iii. Bar Chart iv. Pie Chart 2. Numerical Variable: Insurance Premium (Q5) i. & ii. Frequency Distribution and Percentages ClassFreq%< $600="" 1="" 14="" 31.11="">< $900="" 2="" 9="" 20.00="">< $1200="" 3="" 9="" 20.00="">< $1500="" 4="" 4="" 8.89=""> $15015920.00 Total45100 iii. Range4.00 iv. Mean2.67 v. Median2.00 vi. Standard Dev.1.50 Insurance Premium Mean2.6666666667 Standard Error0.2247332875 Median2 Mode1 Standard Deviation1.5075567229 Sample Variance2.2727272727 Kurtosis-1.2524651163 Skewness0.3933671263 Range4 Minimum1 Maximum5 Sum120 Count45 B. Inferential Statistics 1. Insurance Premium vs. Houshold Income: The correlation is positive and with a magnitude of.65 statistically significant (Significance F<.05) this="" indicates="" that="" if="" your="" insurance="" premium="" is="" higher,="" then="" it="" is="" more="" likely="" that="" your="" household="" income="" is="" high.="" summary="" output="" regression="" statistics="" multiple="" r="" 0.651403561="" r="" square="" 0.4243265993="" adjusted="" r="" square="" 0.4109388458="" standard="" error="" 1.2611364384="" observations="" 45="" anova="" df="" ss="" ms="" f="" significance="" f="" regression="" 1="" 50.41="" 50.41="" 31.6951308671="" 0.00000126="" residual="" 43="" 68.39="" 1.5904651163="" total="" 44="" 118.8="" coefficients="" standard="" error="" t="" stat="" p-value="" lower="" 95%="" upper="" 95%="" lower="" 95.0%="" upper="" 95.0%="" intercept="" 0.7066666667="" 0.385283546="" 1.834147017="" 0.0735581523="" -0.0703316452="" 1.4836649785="" -0.0703316452="" 1.4836649785="" x="" variable1="" 0.71="" 0.1261136438="" 5.6298428812="" 0.00000126="" 0.4556676015="" 0.9643323985="" 0.4556676015="" 0.9643323985="" 2.="" construct="" a="" 95%="" confidence="" interval="" (c.i.)="" for="" "insurance="" premium"="" using="" the="" following="" formula:="" 95%="" c.i.="" equals="" "mean="" +/-="" t*standard="" error"="" we="" are="" using="" t-score="" because="" population="" standard="" deviation="" is="" unknown="" using="" t-table="" on="" page="" 554="" in="" textbook,="" df="n-1=45-1=44," upper="" tail="" area=".025," we="" find="" t="2.015" mean="" 2.67="" standard="" error.="" 0.22="" t="" 2.015="" 95%="" c.i.="" upper="" limit="" 3.11="" lower="" limit="" 2.23="" in="" this="" case="" we="" are="" confident="" that="" 95%="" of="" similarly="" constructed="" intervals="" will="" contain="" the="" true="" population="" mean.="" in="" other="" words,="" we="" are="" 95%="" confident="" that="" the="" true="" population="" mean="" will="" be="" between="" 2.23="" and="" 3.11.="" further="" translation:="" we="" are="" 95%="" confident="" that="" in="" the="" population,="" the="" average="" automobile="" insurance="" premium="" tends="" to="" be="" between="" $900="" to="" $1200="" based="" on="" the="" sample="" we="" have="" obtained.="" extra="" credit="" ec="" 1-1.="" insurance="" premium="" vs.="" purchase="" price:="" the="" correlation="" is="" positive="" and="" with="" a="" magnitude="" of.73="" statistically="" significant="" (significance=""><.05) this="" indicates="" that="" as="" your="" insurance="" premium="" rises,="" more="" likely="" your="" automobile="" purchase="" price="" will="" increase.="" summary="" output="" regression="" statistics="" multiple="" r="" 0.7290544785="" r="" square="" 0.5315204327="" adjusted="" r="" square="" 0.520625559="" standard="" error="" 1.0437851148="" observations="" 45="" anova="" df="" ss="" ms="" f="" significance="" f="" regression="" 1="" 53.1520432692="" 53.1520432692="" 48.7862869604="" 0.0000000135="" residual="" 43="" 46.8479567308="" 1.0894873658="" total="" 44="" 100="" coefficients="" standard="" error="" t="" stat="" p-value="" lower="" 95%="" upper="" 95%="" lower="" 95.0%="" upper="" 95.0%="" intercept="" 0.9615384615="" 0.289493904="" 3.3214463181="" 0.0018338356="" 0.3777183711="" 1.545358552="" 0.3777183711="" 1.545358552="" x="" variable1="" 0.5994591346="" 0.0858243849="" 6.9847181017="" 0.0000000135="" 0.4263777693="" 0.7725404999="" 0.4263777693="" 0.7725404999="" ec="" 1-2.="" purchase="" price="" vs.="" household="" income:="" the="" correlation="" is="" positive="" and="" with="" a="" magnitude="" of.56="" statistically="" significant="" (significance=""><.05) this="" indicates="" that="" as="" your="" automobile="" purchase="" price="" increases,="" more="" likely="" the="" household="" income="" will="" be="" high.="" summary="" output="" regression="" statistics="" multiple="" r="" 0.5597515247="" r="" square="" 0.3133217694="" adjusted="" r="" square="" 0.2973525082="" standard="" error="" 1.3773700403="" observations="" 45="" anova="" df="" ss="" ms="" f="" significance="" f="" regression="" 1="" 37.2226262019="" 37.2226262019="" 19.6203046527="" 0.000063938="" residual="" 43="" 81.5773737981="" 1.8971482279="" total="" 44="" 118.8="" coefficients="" standard="" error="" t="" stat="" p-value="" lower="" 95%="" upper="" 95%="" lower="" 95.0%="" upper="" 95.0%="" intercept="" 1.1730769231="" 0.3820137158="" 3.0707717407="" 0.0036932859="" 0.4026728523="" 1.9434809939="" 0.4026728523="" 1.9434809939="" x="" variable1="" 0.5016526442="" 0.1132531349="" 4.4294813074="" 0.000063938="" 0.2732559334="" 0.7300493551="" 0.2732559334="" 0.7300493551="" ec="" 2.="" construct="" a="" 95%="" confidence="" interval="" (c.i.)="" for="" "gender"="" using="" the="" following="" formula:="" 95%="" c.i.="" equals="" "proportion="" +/-="" z*standard="" error"="" we="" create="" the="" confidence="" interval="" estimate="" for="" the="" population="" proportion="" of="" male.(categorical="" data)="" we="" are="" using="" z-score;="" critical="" value="" from="" the="" standardized="" norminal="" distribution.="" using="" z-table="" on="" page="" 573="" in="" textbook,="" we="" find="" z="1.96" data="" sample="" size="" 45="" number="" of="" male="" 23="" confidence="" level="" 95%="" intermediate="" calculations="" sample="" proportion="" 0.51="" standard="" error.="" 0.07="" z="" value="" 1.96="" 95%="" c.i.="" upper="" limit="" 0.65="" lower="" limit="" 0.37="" in="" this="" case="" we="" are="" confident="" that="" 95%="" of="" similarly="" constructed="" intervals="" will="" contain="" the="" true="" population="" proportion.="" in="" other="" words,="" we="" are="" 95%="" confident="" that="" the="" true="" population="" proportion="" will="" be="" between="" 37%="" and="" 65%.="" further="" translation:="" we="" are="" 95%="" confident="" that="" in="" the="" population,="" the="" actual="" proportion="" of="" male="" tends="" to="" be="" between="" 37%="" to="" 65%="" based="" on="" the="" sample="" we="" have="" obtained.="" m4="" gender="" frequency="" distribution="" category="" frequency="" gender="" frequency="" distribution="" m3="" gender="" percentages/proportions="" q1="" q2="" q3="" q4="" q5="" q6="" d1="" d2="" id="" number="" of="" car="" new="" or="" used="" type="" of="" car="" purchase="" price="" ($)="" insurance="" premium($)="" per="" 6="" month="" household="" income="" ($)="" gender="" age="" grp="" coding="" rules="" 1="0" 2="1" 3="2" 4="3+" 1="NEW" 2="USED" 1="SEDAN" 2="SUV" 3="SPORTS" car="" 4="NONE" 5="OTHER" 1=""><15000 2=""><25000 3=""><35000 4=""><45000 5=""><55000 6="">549991=<600 2=""><900 3=""><1200 4=""><1500 5="">14991=<25000 2=""><50000 3=""><75000 4=""><90000 5="">899991=FEMALE 2= MALE1=15TO24 2=25TO34 3=35TO44 4=45TO54 5=55TO64 6=65+ 141522421 222315511 322111122 4421,523513 531,21,522316 6411,2,545415 7311,23,65524 842111112 922111122 1012311111 1121133111 12311,222513 13421,31,22126 1421123111 1522111122 16411,31,2,3511 1731233112 1842111211 1941,21,2,33,55511 2041,21,52,34413 211133322 2222111121 2332335121 2442112121 2521333222 2621122112 2722511122 2821133422 29311,23,55513 3021333212 3141,21,3,51,2,34414 3214111 33311,32,34325 342112311 35411,2,54,55514 36311,321311 372111122 3821121222 39411,265524 4031,21,321322 4122312121 4221122122 43311,224514 4421522322 4541121322