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2.2.2 The median incomes fernales each state of the United States, including the Distric of Columbia and Puerto Rico, are givenir table #2.2 10(' "Mediar income of,' 2013). Create frequency distribution, relative frequency distribution, and cumulative frequency distribution using classes. Table #2.2.10: Data Mediar Income for Females $31,862 $40,550 $36,048 $30,752 $41,817 $40,236 $47,476 $40,500 $60,332 $33,823 $35,438 $37,242 $31,238 $39,150 $34,023 $33,745 $33,269 $29,548 $33,865 $31,067 $33,424 $35,484 $41,021 $47,155 $32,316 $42,113 $33,4 $32,462 $35,746 $31,274 $36,027 $37,089 $22,117 $41,412 $31,330 531,32 $33,184 $35,301 $32,843 $38,177 $40,969 $40,993 $29,688 $35,890 $34,381 2.2.6 Create histogram and relative frequency histogram for the data in table $2.2.10 Describe the shape and any findings you can from the graph. 2.2.10 Create ogive for the data table #2. .10. Describe any findings you car from the graph. 2.3.4 Table 7 contains the value of the house and amountof rental income inayearthat the house brings "Capital and rental," 2013). Create scatter plot and state fthereis relationship between the value the house and the annual rental income. Table#2. 3.7: Data House Value versus Rental Value Rental Value Rental Value Rental Value Rental 81000 77000 4576 75000 7280 67500 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 130000 9776 126000 125000 140000 9568 140000 135000 7488 13312 165000 8528 155000 148000 8320 178000 11856 174000 10400 170000 9568 170000 2688 200000 12272 200000 10608 194000 11232 190000 8320 214000 8528 208000 10400 200000 10400 200000 8320 240000 10192 240000 12064 240000 11648 225000 12480 289000 11648 270000 12896 262000 244500 325000 12480 12272 300000 2.3.8 The economic of 2008 affected though some more than others. Some people in Australia wasn't badly fromthe crisis. The bank assets billions of Australia dollars (AUD))of the Reserve Bank Australia (RBA) the time periodo March 2007 through March 2013 containedin l'B1 assets of," 2013). Create time-series plot and interpret findings Table#2.3.11: Data Date versus Assets in billions ot Date AUD Mar-2006 -2006 -2007 134.0 123.0 2008 105.6 101.5 2008 158.8 2009 118.7 87.0 86. 83.4 85.7 74.8 83.9 95.8 Mar-2013 90.5 3.1.2 The lengths (in kilometers) of rivers on the South Island of New Zealand that flow to the Pacific Ocean are listed table #3.1. (Lee, 1994). Find the mean median, and mode. Table #3 .1.8 Lengths of Rivers (km) Flowing to Pacific Ocean River Length River Length (km) (km) Clarence 209 Clutha Conway Taieri 288 Waiau 169 Shag Hurunui Kakanui 64 Waipara Rangitata 121 Ashley 97 Ophi 80 Waimakariri 161 Pareora 56 Selwyn 95 Waihao 64 Rakaia 145 Waitaki 209 Ashburton 90 3.1.8 State which type of measurement scale each represents and then which center measures can be use for the variable? a.) You collect data on the height of plants using new fertilizer. b.) You collect data on the cars that people drivei Campbelltown Australia c.) You collect data on the temperature at differen locations Antarctica d.) You collect data on the first. second, and third winner beer competition 3.1.12 An employee Coconino Community College (CCC) evaluated based ongoal setting and accomolishments toward goals joh effectiveness competencies. CCC core values. Suppose for specific employee, goal has weight 20% goal 2has weight goal has weight 10%job effectiveness weight 25% competency 1 has goal 4%, competency 2has agoal has weight of 3%, competency has weight competency 4 has : weight of 5% values has weight of 10% Suppose employee scores F2.0for goal 1 2.0 for goal 2, 4.0 for goal 3, 3.0 for job effectiveness, 2.0 for competency 3.0 for competency 2,20for competency 3, 3.0 for competeno 4, and 4.0 for core values. Find the weighted average score for this employee. If an employee that has a score less than 1.5. they must have Performance Enhancement Plan written. Does this employee need aplan? 3.2.2 The lengths (in kilometers) of ivers on the South Island of New Zealand that flow the Pacific Ocean are listedintable #3.2.9 (Lee. 1994). Table #3.2.9: Lengths Rivers (km) Flowing Pacific Ocean River Length River Length (km) (km) Clarence 209 Clutha Conway Taieri 288 Waiau 169 Shag Hurunui 138 Kakanu 64 Waipara 64 Waitaki 209 Ashley Waihao 64 Wairnakariri 161 Pareora Selwyn 95 Rangitata Rakaia 145 Ophi 80 Ashburton 90 a.) Find mean and median b.) Find range. c.) Find the variance and standard deviation 3.2.6 Print- Matic printing company spends specific amounts on fixed costs every month. The costs of those fixed costs are intable #3.2.13. Table #3.: .13: Fixed Costs for Print Matic Printing Company Monthly charges Monthly cost($) Bank charges Cleaning 2208 Computer expensive Lease payments Postage Uniforms a.) Find mean and median. Find the range c.) Find variance and deviation

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## 2.2.2

```{r}
class1 <- c(31862, 40550, 36048, 30752, 41817, 40236, 47476, 40500)
class2 <- c(60332, 33823, 35438, 37242, 31238, 39150, 34023, 33745)
class3 <- c(33269, 32684, 31844, 34599, 48748, 46185, 36931, 40416)
class4 <- c(29548, 33865, 31067, 33424, 35484, 41021, 47155, 32316)
class5 <- c(42113, 33459, 32462, 35746, 31274, 36027, 37089, 22117)
class6 <- c(41412, 31330, 31329, 33184, 35301, 32843, 38177, 40969)
class7 <- c(40993, 29688, 35890, 34381)

all_classes <- c(class1, class2, class3, class4, class5, class6, class7)

# Frequency Distribution
classes_freq_dist <- table(all_classes)
classes_freq_dist

# Cumulative Frequency Distribution
classes_cumm_dist <- cumsum(classes_freq_dist)
classes_cumm_dist

# Relative Frequency Distribution
classes_rel_dist <- classes_freq_dist/length(unique(all_classes))
classes_rel_dist
```

## 2.2.6

```{r}
hist(all_classes)
```

Histogram shows data is right skewed. It shows data is mostly distributed between in the range of 30000 and 40000. There is an outlier beyond 60000.

```{r}
hist(classes_rel_dist)
```

Since, each data is unique so relative distrubution is constant ie. 0.01923077....

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