• Perform a simple linear regressionwith dependent variable (cost) and independent variable (age).

cost	age
13316	83
14043	72
17354	64
15338	81
14510	77
14703	81
17422	64
16958	69
12873	82
12185	68
10096	64
13787	71
29478	73
15900	74
16030	67
16037	78
11163	72
15974	78
15055	75
18636	84
9063	61
18247	65
14216	72
14881	75
17133	80
13668	82
15142	76
10834	66
10321	70
13906	81
18759	77
12974	69
17186	81
17262	63
17030	76
15655	68
16662	79
10036	62
16471	69
16269	79
17714	65
15179	68
29408	90
16060	63
15980	78
12265	68
14254	80
15594	74
13452	73
12095	67
14817	75
18176	68
14847	69
14624	74
18471	83
13785	83
13380	70
14227	73
13824	73
11915	81
18384	62
16575	79
15453	64
13527	63
16285	64
15307	76
14514	75
12579	68
14772	74
15122	63
15473	75
15719	82
15123	76
16091	78
14874	67
14679	74
13380	74
17630	82
16704	80
13428	70
12101	83
13571	71
13117	70
12183	77
14181	82
15484	76
14478	74
16057	78
15577	63
14588	74
16739	80
15358	82
13913	65
14125	84
12880	69
15720	63
16391	77
15230	82
15972	67
16008	78
15702	67
13049	87
10734	82
18683	86
18203	78
14154	61
14263	73
14163	72
12866	69
12349	68
14472	73
11520	66
14927	75
12136	67
13981	70
11401	73
12852	69
13749	71
13861	67
14603	74
14336	62
13335	70
14400	73
15754	77
16600	63
12758	69
14797	82
14520	74
12959	69
17617	81
12974	69
14981	75
15989	78
14886	75
11331	65
15457	77
14366	73
14083	72
14247	73
15539	82
15190	74
28764	86
10596	77
13844	71
14636	63
14887	82
14232	73
14508	62
12702	81
16195	78
13793	77
12184	67
15796	74
12607	68
13368	83
14787	76
16267	61
17924	82
12524	81
16437	79
14610	69
15227	76
15197	75
13945	72
13461	70
13588	63
14413	74
15600	77
13969	72
15903	74
13549	71
15694	77
17127	67
15257	76
16370	67
14542	62
16317	79
16846	80
14063	72
13904	71
12988	70
16284	79
15128	76
11164	66
16788	70

• Interpret the statistical significance and effect size of the regression coefficients.
• Discuss what the regression means in practical terms.